├── .gitignore ├── CODE_OF_CONDUCT.md ├── CONTRIBUTING.md ├── LICENSE ├── README.md ├── ac1-markdown ├── basic_descriptive_statistics │ ├── count_and_sum.md │ ├── figures │ │ ├── average_student_exam_scores_skew.png │ │ ├── cell_A1.png │ │ ├── cells_A1_A6.png │ │ ├── cells_A1_D1.png │ │ ├── cells_A1_D6.png │ │ ├── city_income.png │ │ ├── consistentville_and_wonkytown.png │ │ ├── distance_statistic.png │ │ ├── height_statistic.png │ │ ├── match.png │ │ ├── minimum_using_cell_range.png │ │ ├── minimum_using_values.png │ │ ├── right_skew_histogram.png │ │ ├── sea_max_average.png │ │ ├── seattle.png │ │ ├── sheet_example.png │ │ ├── standard_deviation_in_histograms.png │ │ ├── statistics_summary.png │ │ ├── student_heights_outlier.png │ │ ├── test_scores.png │ │ ├── uneven_dice_mean.png │ │ └── uneven_dice_median.png │ ├── introduction.md │ ├── measures_of_center.md │ ├── measures_of_spread.md │ ├── minimum_and_maximum.md │ ├── outliers_and_skew.md │ ├── summary.md │ ├── toctree.md │ ├── variables.md │ └── what_is_a_statistic.md ├── filtering_and_grouping │ ├── figures │ │ ├── create_a_filter.png │ │ ├── filter_french_painters.png │ │ ├── filter_over_200_paintings.png │ │ ├── filter_painters_with_any_french_nationality.png │ │ ├── filtered_french_painters.png │ │ ├── filtered_index.png │ │ ├── french_painters_using_countif.png │ │ ├── french_painters_with_over_200_paintings.png │ │ ├── painters_sort_genre.png │ │ ├── painters_sort_paintings.png │ │ ├── spotify_averageif_example.png │ │ ├── summary.png │ │ ├── table_countif_example.png │ │ ├── table_data.png │ │ ├── table_filter_example.png │ │ ├── table_group_example.png │ │ ├── table_sumif_example.png │ │ ├── titanic_adding_survived_column.png │ │ └── titanic_men_survival_rate.png │ ├── filtering_data.md │ ├── grouping_data.md │ ├── introduction.md │ ├── summary.md │ └── toctree.md ├── importing_and_exporting_data │ ├── exporting_data.md │ ├── figures │ │ ├── cereal_data.png │ │ ├── csv_example.png │ │ ├── import_example.png │ │ ├── importing_exporting_summary.png │ │ ├── publish_data.png │ │ ├── separatortype_example.png │ │ ├── ssv_example.png │ │ ├── tsv_example.png │ │ └── upload_example.png │ ├── importing_data.md │ ├── summary.md │ └── toctree.md ├── introduction_to_visualizations │ ├── creating_visualizations_checklist.md │ ├── example_visualizations.md │ ├── figures │ │ ├── bar_chart_example.png │ │ ├── color_blind.png │ │ ├── country_population.png │ │ ├── creating_visualizations_checklist.png │ │ ├── example_pie_chart.png │ │ ├── favorite_ice_cream.png │ │ ├── not_color_blind.png │ │ ├── sheets_how_to.png │ │ ├── student_grades.png │ │ ├── summary.png │ │ ├── table_data_example.png │ │ ├── train_arrivals.png │ │ └── visualization_checklist.png │ ├── histograms_and_bar_charts.md │ ├── introduction.md │ ├── reading_visualizations_checklist.md │ ├── summary.md │ └── toctree.md ├── manipulating_data │ ├── figures │ │ ├── adding_a_variable_pivot.png │ │ ├── alzheimers.png │ │ ├── alzheimers_california.png │ │ ├── death_bar_chart.png │ │ ├── death_percentage.png │ │ ├── death_percentage_time.png │ │ ├── death_rate_column.png │ │ ├── death_sums.png │ │ ├── employee_table.png │ │ ├── grocery_image.png │ │ ├── jan_meyers.png │ │ ├── leading_cause_of_death.png │ │ ├── line_chart.png │ │ ├── manipulating_data_summary.png │ │ ├── median_age_death_rate.png │ │ ├── pivot_deaths.png │ │ ├── pivot_table_add_year.png │ │ ├── pivot_table_cause_name.png │ │ ├── pivot_table_column_chart.png │ │ ├── pivot_table_column_correct_cells.png │ │ ├── pivot_table_complete_death_pivot.png │ │ ├── pivot_table_death_summary.png │ │ ├── pivot_table_editor.png │ │ ├── pivot_table_filter_alzheimers.png │ │ ├── pivot_table_filter_california.png │ │ ├── pivot_table_filter_cn.png │ │ ├── pivot_table_filter_date.png │ │ ├── pivot_table_filter_state.png │ │ ├── pivot_table_insert_chart.png │ │ ├── pivot_table_select_data.png │ │ ├── pivot_table_select_row.png │ │ ├── pivot_table_select_values_cs.png │ │ ├── pivot_table_select_values_hours.png │ │ ├── pivot_table_select_values_os.png │ │ ├── pivot_table_select_values_summary.png │ │ ├── pivot_table_subset_example.png │ │ ├── pivot_table_total_enabled.png │ │ ├── pivot_table_value_death.png │ │ ├── sum_death_states.png │ │ ├── two_dim_pivot_table.png │ │ ├── us_population_by_year.png │ │ ├── vlookup.png │ │ └── vlookup_death.png │ ├── introduction.md │ ├── joining_data.md │ ├── pivot_tables.md │ ├── summary.md │ └── toctree.md ├── module_a_preface.md ├── module_b_preface.md ├── module_c_preface.md ├── projects │ ├── module_a.md │ ├── module_b.md │ ├── module_c.md │ └── toctree.md ├── regression_and_line_of_best_fit │ ├── creating_line_of_best_fit.md │ ├── equation_of_a_line_refresher.md │ ├── figures │ │ ├── SAT_Math_and_Earnings.png │ │ ├── Slope_Changes_colored.jpg │ │ ├── Slope_Changes_for_SAT_math_colored.jpg │ │ ├── add_trendline.png │ │ ├── average_sat_score_completion_rate.png │ │ ├── completion_rate_loans.png │ │ ├── edit_chart.png │ │ ├── equation_of_a_line.png │ │ ├── fix_juneau_data_point.png │ │ ├── jan_temp_3.png │ │ ├── january_temperatures.png │ │ ├── january_temperatures_decreasing.png │ │ ├── january_temperatures_decreasing2.png │ │ ├── mean_jan_temp.png │ │ ├── median_sat_earnings_annotated.png │ │ ├── negative_slope.png │ │ ├── outlier_jan_temp.png │ │ ├── outlier_jan_temp_line.png │ │ ├── overfit_example.png │ │ ├── overfit_linear_regression_example.png │ │ ├── overfitting_graph.png │ │ ├── polynomial_curve.png │ │ ├── positive_slope.png │ │ ├── regression_summary.png │ │ ├── sat_completion_rate_annotated.png │ │ ├── sheets_trendline.png │ │ └── trendline_type.png │ ├── interpreting_slope.md │ ├── introduction.md │ ├── making_predictions_with_the_regression_line.md │ ├── nonlinear_regression.md │ ├── outliers.md │ ├── summary.md │ └── toctree.md ├── scatter_plots_and_correlation │ ├── correlation.md │ ├── correlation_and_college_data.md │ ├── correlation_and_filtering.md │ ├── correlation_versus_causation.md │ ├── creating_a_scatter_plot_in_sheets.md │ ├── describing_scatter_plots.md │ ├── figures │ │ ├── avg_if.png │ │ ├── avg_temp_region_jan.png │ │ ├── city_region_breakdown.png │ │ ├── college_data.png │ │ ├── correlations_example.png │ │ ├── create_a_scatter_axistitle1.png │ │ ├── create_a_scatter_copy_data.png │ │ ├── create_a_scatter_horizontal_label.png │ │ ├── create_a_scatter_insert_chart.png │ │ ├── create_a_scatter_plot_choose_scatter.png │ │ ├── create_a_scatter_title.png │ │ ├── create_a_scatter_top_label.png.png │ │ ├── create_a_scatter_vertical_label.png │ │ ├── create_a_scatter_xaxis1.png │ │ ├── create_a_scatter_xaxis2.png │ │ ├── create_a_scatter_yaxis1.png │ │ ├── create_a_scatter_yaxis2.png │ │ ├── example_scatterplot.png │ │ ├── january_scatterplot.png │ │ ├── lat_temp_histograms.png │ │ ├── latitude_vs_temp.png │ │ ├── mult_choice_plots.png │ │ ├── mult_choice_plots_abstract.png │ │ ├── participant_improvement.png │ │ ├── pushup_graph_and_data.png │ │ ├── scatter-correlation-graph-1.png │ │ ├── scatter-correlation-graph-2.png │ │ ├── scatter-correlation-graph-3.png │ │ ├── scatter1.png │ │ ├── scatter2.png │ │ ├── scatter3.png │ │ ├── scatter_plots_correlation_question.png │ │ └── summary.png │ ├── introduction.md │ ├── motivating_scatterplots.md │ ├── scatter_plots.md │ ├── summary.md │ └── toctree.md ├── sheets_basics │ ├── errors.md │ ├── figures │ │ ├── chocolate_cake_amounts_for_custom_servings.png │ │ ├── chocolate_cake_custom_servings.png │ │ ├── chocolate_cake_flour_for_18_servings.png │ │ ├── chocolate_cake_flour_for_custom_servings.png │ │ ├── chocolate_cake_relative_referencing_not_working.png │ │ ├── painters_example_sheets.png │ │ ├── sheet_example.png │ │ ├── sheets_error.png │ │ ├── sheets_keyword_definitions.png │ │ └── sheets_summary.png │ ├── introduction.md │ ├── summary.md │ ├── toctree.md │ ├── what_is_a_formula.md │ └── what_is_a_sheet.md └── sql │ ├── aggregating.md │ ├── figures │ ├── bike_dataset_columns.png │ └── summary.png │ ├── filtering.md │ ├── how_to_run_sql.md │ ├── ifs_and_cases.md │ ├── introduction.md │ ├── joining.md │ ├── selecting.md │ ├── sorting.md │ ├── summary.md │ └── toctree.md ├── ac1 ├── _sources │ ├── basic_descriptive_statistics │ │ ├── count_and_sum.rst │ │ ├── figures │ │ │ ├── average_student_exam_scores_skew.png │ │ │ ├── cell_A1.png │ │ │ ├── cells_A1_A6.png │ │ │ ├── cells_A1_D1.png │ │ │ ├── cells_A1_D6.png │ │ │ ├── city_income.png │ │ │ ├── consistentville_and_wonkytown.png │ │ │ ├── distance_statistic.png │ │ │ ├── height_statistic.png │ │ │ ├── match.png │ │ │ ├── minimum_using_cell_range.png │ │ │ ├── minimum_using_values.png │ │ │ ├── right_skew_histogram.png │ │ │ ├── sea_max_average.png │ │ │ ├── seattle.png │ │ │ ├── sheet_example.png │ │ │ ├── standard_deviation_in_histograms.png │ │ │ ├── statistics_summary.png │ │ │ ├── student_heights_outlier.png │ │ │ ├── test_scores.png │ │ │ ├── uneven_dice_mean.png │ │ │ └── uneven_dice_median.png │ │ ├── introduction.rst │ │ ├── measures_of_center.rst │ │ ├── measures_of_spread.rst │ │ ├── minimum_and_maximum.rst │ │ ├── outliers_and_skew.rst │ │ ├── summary.rst │ │ ├── toctree.rst │ │ ├── variables.rst │ │ └── what_is_a_statistic.rst │ ├── filtering_and_grouping │ │ ├── figures │ │ │ ├── create_a_filter.png │ │ │ ├── filter_french_painters.png │ │ │ ├── filter_over_200_paintings.png │ │ │ ├── filter_painters_with_any_french_nationality.png │ │ │ ├── filtered_french_painters.png │ │ │ ├── filtered_index.png │ │ │ ├── filtering_summary.png │ │ │ ├── french_painters_using_countif.png │ │ │ ├── french_painters_with_over_200_paintings.png │ │ │ ├── painters_sort_genre.png │ │ │ ├── painters_sort_paintings.png │ │ │ ├── spotify_averageif_example.png │ │ │ ├── table_countif_example.png │ │ │ ├── table_data.png │ │ │ ├── table_filter_example.png │ │ │ ├── table_group_example.png │ │ │ ├── table_sumif_example.png │ │ │ ├── titanic_adding_survived_column.png │ │ │ └── titanic_men_survival_rate.png │ │ ├── filtering_data.rst │ │ ├── grouping_data.rst │ │ ├── introduction.rst │ │ ├── summary.rst │ │ └── toctree.rst │ ├── importing_and_exporting_data │ │ ├── exporting_data.rst │ │ ├── figures │ │ │ ├── cereal_data.png │ │ │ ├── csv_example.png │ │ │ ├── import_example.png │ │ │ ├── importing_summary.png │ │ │ ├── publish_data.png │ │ │ ├── separatortype_example.png │ │ │ ├── ssv_example.png │ │ │ ├── tsv_example.png │ │ │ └── upload_example.png │ │ ├── importing_data.rst │ │ ├── summary.rst │ │ └── toctree.rst │ ├── index.rst │ ├── introduction_to_visualizations │ │ ├── creating_visualizations_checklist.rst │ │ ├── example_visualizations.rst │ │ ├── figures │ │ │ ├── bar_chart_example.png │ │ │ ├── color_blind.png │ │ │ ├── country_population.png │ │ │ ├── creating_visualizations_checklist.png │ │ │ ├── example_pie_chart.png │ │ │ ├── favorite_ice_cream.png │ │ │ ├── not_color_blind.png │ │ │ ├── sheets_how_to.png │ │ │ ├── student_grades.png │ │ │ ├── table_data_example.png │ │ │ ├── train_arrivals.png │ │ │ ├── visualization_checklist.png │ │ │ └── visualizations_summary.png │ │ ├── histograms_and_bar_charts.rst │ │ ├── introduction.rst │ │ ├── reading_visualizations_checklist.rst │ │ ├── summary.rst │ │ └── toctree.rst │ ├── manipulating_data │ │ ├── figures │ │ │ ├── adding_a_variable_pivot.png │ │ │ ├── alzheimers.png │ │ │ ├── alzheimers_california.png │ │ │ ├── death_bar_chart.png │ │ │ ├── death_percentage.png │ │ │ ├── death_percentage_time.png │ │ │ ├── death_rate_column.png │ │ │ ├── death_sums.png │ │ │ ├── employee_table.png │ │ │ ├── grocery_image.png │ │ │ ├── jan_meyers.png │ │ │ ├── leading_cause_of_death.png │ │ │ ├── line_chart.png │ │ │ ├── manipulating_summary.png │ │ │ ├── median_age_death_rate.png │ │ │ ├── pivot_deaths.png │ │ │ ├── pivot_table_add_year.png │ │ │ ├── pivot_table_cause_name.png │ │ │ ├── pivot_table_column_chart.png │ │ │ ├── pivot_table_column_correct_cells.png │ │ │ ├── pivot_table_complete_death_pivot.png │ │ │ ├── pivot_table_death_summary.png │ │ │ ├── pivot_table_editor.png │ │ │ ├── pivot_table_filter_alzheimers.png │ │ │ ├── pivot_table_filter_california.png │ │ │ ├── pivot_table_filter_cn.png │ │ │ ├── pivot_table_filter_date.png │ │ │ ├── pivot_table_filter_state.png │ │ │ ├── pivot_table_insert_chart.png │ │ │ ├── pivot_table_select_data.png │ │ │ ├── pivot_table_select_row.png │ │ │ ├── pivot_table_select_values_cs.png │ │ │ ├── pivot_table_select_values_hours.png │ │ │ ├── pivot_table_select_values_os.png │ │ │ ├── pivot_table_select_values_summary.png │ │ │ ├── pivot_table_subset_example.png │ │ │ ├── pivot_table_total_enabled.png │ │ │ ├── pivot_table_value_death.png │ │ │ ├── sum_death_states.png │ │ │ ├── two_dim_pivot_table.png │ │ │ ├── us_population_by_year.png │ │ │ ├── vlookup.png │ │ │ └── vlookup_death.png │ │ ├── introduction.rst │ │ ├── joining_data.rst │ │ ├── pivot_tables.rst │ │ ├── summary.rst │ │ └── toctree.rst │ ├── module_a_preface.rst │ ├── module_b_preface.rst │ ├── module_c_preface.rst │ ├── projects │ │ ├── module_a.rst │ │ ├── module_b.rst │ │ ├── module_c.rst │ │ └── toctree.rst │ ├── regression_and_line_of_best_fit │ │ ├── creating_line_of_best_fit.rst │ │ ├── equation_of_a_line_refresher.rst │ │ ├── figures │ │ │ ├── SAT_Math_and_Earnings.png │ │ │ ├── Slope_Changes_colored.jpg │ │ │ ├── Slope_Changes_for_SAT_math_colored.jpg │ │ │ ├── add_trendline.png │ │ │ ├── average_sat_score_completion_rate.png │ │ │ ├── completion_rate_loans.png │ │ │ ├── edit_chart.png │ │ │ ├── equation_of_a_line.png │ │ │ ├── fix_juneau_data_point.png │ │ │ ├── jan_temp_3.png │ │ │ ├── january_temperatures.png │ │ │ ├── january_temperatures_decreasing.png │ │ │ ├── january_temperatures_decreasing2.png │ │ │ ├── mean_jan_temp.png │ │ │ ├── median_sat_earnings_annotated.png │ │ │ ├── negative_slope.png │ │ │ ├── outlier_jan_temp.png │ │ │ ├── outlier_jan_temp_line.png │ │ │ ├── overfit_example.png │ │ │ ├── overfit_linear_regression_example.png │ │ │ ├── overfitting_graph.png │ │ │ ├── polynomial_curve.png │ │ │ ├── positive_slope.png │ │ │ ├── regression_summary.png │ │ │ ├── sat_completion_rate_annotated.png │ │ │ ├── sheets_trendline.png │ │ │ └── trendline_type.png │ │ ├── interpreting_slope.rst │ │ ├── introduction.rst │ │ ├── making_predictions_with_the_regression_line.rst │ │ ├── nonlinear_regression.rst │ │ ├── outliers.rst │ │ ├── summary.rst │ │ └── toctree.rst │ ├── scatter_plots_and_correlation │ │ ├── correlation.rst │ │ ├── correlation_and_college_data.rst │ │ ├── correlation_and_filtering.rst │ │ ├── correlation_versus_causation.rst │ │ ├── creating_a_scatter_plot_in_sheets.rst │ │ ├── describing_scatter_plots.rst │ │ ├── figures │ │ │ ├── avg_if.png │ │ │ ├── avg_temp_region_jan.png │ │ │ ├── city_region_breakdown.png │ │ │ ├── college_data.png │ │ │ ├── correlations_example.png │ │ │ ├── create_a_scatter_axistitle1.png │ │ │ ├── create_a_scatter_copy_data.png │ │ │ ├── create_a_scatter_horizontal_label.png │ │ │ ├── create_a_scatter_insert_chart.png │ │ │ ├── create_a_scatter_plot_choose_scatter.png │ │ │ ├── create_a_scatter_title.png │ │ │ ├── create_a_scatter_top_label.png.png │ │ │ ├── create_a_scatter_vertical_label.png │ │ │ ├── create_a_scatter_xaxis1.png │ │ │ ├── create_a_scatter_xaxis2.png │ │ │ ├── create_a_scatter_yaxis1.png │ │ │ ├── create_a_scatter_yaxis2.png │ │ │ ├── example_scatterplot.png │ │ │ ├── january_scatterplot.png │ │ │ ├── lat_temp_histograms.png │ │ │ ├── latitude_vs_temp.png │ │ │ ├── mult_choice_plots.png │ │ │ ├── mult_choice_plots_abstract.png │ │ │ ├── participant_improvement.png │ │ │ ├── pushup_graph_and_data.png │ │ │ ├── scatter-correlation-graph-1.png │ │ │ ├── scatter-correlation-graph-2.png │ │ │ ├── scatter-correlation-graph-3.png │ │ │ ├── scatter1.png │ │ │ ├── scatter2.png │ │ │ ├── scatter3.png │ │ │ ├── scatter_plots_correlation_question.png │ │ │ └── scatter_plots_summary.png │ │ ├── introduction.rst │ │ ├── motivating_scatterplots.rst │ │ ├── scatter_plots.rst │ │ ├── summary.rst │ │ └── toctree.rst │ ├── sheets_basics │ │ ├── errors.rst │ │ ├── figures │ │ │ ├── chocolate_cake_amounts_for_custom_servings.png │ │ │ ├── chocolate_cake_custom_servings.png │ │ │ ├── chocolate_cake_flour_for_18_servings.png │ │ │ ├── chocolate_cake_flour_for_custom_servings.png │ │ │ ├── chocolate_cake_relative_referencing_not_working.png │ │ │ ├── painters_example_sheets.png │ │ │ ├── sheet_example.png │ │ │ ├── sheets_error.png │ │ │ ├── sheets_keyword_definitions.png │ │ │ └── sheets_summary.png │ │ ├── introduction.rst │ │ ├── summary.rst │ │ ├── toctree.rst │ │ ├── what_is_a_formula.rst │ │ └── what_is_a_sheet.rst │ └── sql │ │ ├── aggregating.rst │ │ ├── figures │ │ ├── bike_dataset_columns.png │ │ └── sql_summary.png │ │ ├── filtering.rst │ │ ├── how_to_run_sql.rst │ │ ├── ifs_and_cases.rst │ │ ├── introduction.rst │ │ ├── joining.rst │ │ ├── selecting.rst │ │ ├── sorting.rst │ │ ├── summary.rst │ │ └── toctree.rst ├── _static │ └── bikeshare.db ├── conf.py ├── pavement.py └── sphinx_settings.json └── documentation ├── ac1_course_guide.md ├── ac1_instructor_guide.md ├── content_development.md ├── discussion_guide.md ├── images ├── fixes_issue.png ├── new_pull_request.png ├── related_issue.png └── reviewers.png ├── runestone_serve.md └── style_guide.md /.gitignore: -------------------------------------------------------------------------------- 1 | build 2 | published 3 | __pycache__ 4 | sphinx-enki-info.txt 5 | sphinx_settings.json 6 | -------------------------------------------------------------------------------- /CONTRIBUTING.md: -------------------------------------------------------------------------------- 1 | # How to Contribute 2 | 3 | We'd love to accept your patches and contributions to this project. There are 4 | just a few small guidelines you need to follow. 5 | 6 | ## Contributor License Agreement 7 | 8 | Contributions to this project must be accompanied by a Contributor License 9 | Agreement. You (or your employer) retain the copyright to your contribution; 10 | this simply gives us permission to use and redistribute your contributions as 11 | part of the project. Head over to to see 12 | your current agreements on file or to sign a new one. 13 | 14 | You generally only need to submit a CLA once, so if you've already submitted one 15 | (even if it was for a different project), you probably don't need to do it 16 | again. 17 | 18 | ## Code reviews 19 | 20 | All submissions, including submissions by project members, require review. We 21 | use GitHub pull requests for this purpose. Consult 22 | [GitHub Help](https://help.github.com/articles/about-pull-requests/) for more 23 | information on using pull requests. 24 | 25 | ## Community Guidelines 26 | 27 | This project follows 28 | [Google's Open Source Community Guidelines](https://opensource.google.com/conduct/). 29 | -------------------------------------------------------------------------------- /ac1-markdown/basic_descriptive_statistics/figures/average_student_exam_scores_skew.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/basic_descriptive_statistics/figures/average_student_exam_scores_skew.png -------------------------------------------------------------------------------- /ac1-markdown/basic_descriptive_statistics/figures/cell_A1.png: -------------------------------------------------------------------------------- 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Using statistics is so popular 11 | because they provide evidence and credibility to claims. 12 | 13 | Here are just a few examples of how a variety of fields use statistics: 14 | 15 | - Journalists use data to substantiate their reporting. 16 | - Political leaders use data to inform their decisions. 17 | - Sports teams and businesses lean heavily on statistical algorithms 18 | for their actions. 19 | - Psychologists use statistics to give meaning to the data they 20 | collected. 21 | 22 | As much as statistics are used, statistics are also frequently misused. 23 | One of the most important mediums in which statistics are often misused 24 | is the news. Since the claims made in the news often impact the world 25 | around you, it's important for you to be able to critically assess those 26 | statistics. 27 | 28 | Consider the following two sentences: 29 | 30 | 1. "Americans are spending a lot of time watching TV." 31 | 2. "Adult Americans are spending on average five hours and four minutes 32 | watching TV per day." 33 | 34 | Although both sentences make the same point, the statistic used in the 35 | second sentence makes the claim much more specific than the first. The 36 | specificity provided by statistics is a powerful tool that allows you to 37 | support your own claims or drive your own decision-making in any field 38 | of work or study. 39 | -------------------------------------------------------------------------------- /ac1-markdown/basic_descriptive_statistics/summary.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | 7 | 8 | ![Graphic summarizing key concepts of basic descriptive statistics.](figures/statistics_summary.png) -------------------------------------------------------------------------------- /ac1-markdown/basic_descriptive_statistics/toctree.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Basic Descriptive Statistics 7 | ============================ 8 | 9 | Contents 10 | -------- 11 | 12 | [Introduction](introduction.md) 13 | 14 | [What is a statistic](what_is_a_statistic.md) 15 | 16 | [Variables](variables.md) 17 | 18 | [Count and sum](count_and_sum.md) 19 | 20 | [Minimum and maximum](minimum_and_maximum.md) 21 | 22 | [Measures of center](measures_of_center.md) 23 | 24 | [Outliers and skew](outliers_and_skew.md) 25 | 26 | [Measures of spread](measures_of_spread.md) 27 | 28 | [Summary](summary.md) 29 | 30 | -------------------------------------------------------------------------------- /ac1-markdown/basic_descriptive_statistics/what_is_a_statistic.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | 'What Is A Statistic?' 7 | ====================== 8 | 9 | Many people discuss statistics, but not everyone knows what a statistic 10 | actually is. 11 | 12 | #### Statistic Definition 13 | 14 | **A statistic is a fact of the data.** A statistic is any piece of 15 | information you can get from a set of data. 16 | 17 | For example, suppose you have a dataset containing the heights of all 18 | students in this class. 19 | 20 | ![image](figures/height_statistic.png) 21 | 22 | The following are all statistics from that dataset. 23 | 24 | - The shortest height is 146cm. 25 | - The tallest height is 192cm. 26 | - There are 19 students in this class. 27 | - The average height is 166.16cm. 28 | - The sum of all heights in the class is 3157cm. 29 | - Half the maximum height is 96cm. 30 | 31 | Some statistics are more common and useful than others. For example, 32 | knowing the average height will likely be more useful in real life than 33 | knowing the sum of all heights. This chapter will guide you through the 34 | most common descriptive statistics. 35 | 36 | Suppose you have a dataset on how far students travel to get to school. 37 | 38 | ![image](figures/distance_statistic.png) 39 | 40 | ### Short answer 41 | 42 | - What are some important statistics of the dataset above? -------------------------------------------------------------------------------- /ac1-markdown/filtering_and_grouping/figures/create_a_filter.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/filtering_and_grouping/figures/create_a_filter.png -------------------------------------------------------------------------------- /ac1-markdown/filtering_and_grouping/figures/filter_french_painters.png: -------------------------------------------------------------------------------- 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Sheets has 11 | functions that allow you to **filter** as well as **group** data. For 12 | example, if you had the table below you could use filtering and grouping 13 | to more easily display certain data. 14 | 15 | ![Table containing basic data for 23 people.](figures/table_data.png) 16 | 17 | Above is a table with some standard information collected from a group 18 | of 23 people. This data is fictional. Below is the same data from this 19 | table after filtering and grouping are separately applied. 20 | 21 | ![The same table after applying a filter.](figures/table_filter_example.png) 22 | 23 | This is an example of **filtering** the data to only see rows of people 24 | whose city is Los Angeles. 25 | 26 | ![The same table after applying grouping.](figures/table_group_example.png) 27 | 28 | This is an example of **grouping** the data to count the number of 29 | people in this dataset who are from Los Angeles. 30 | 31 | Don\'t worry if this is confusing. These examples are meant to help you 32 | become more familiar with applications of filtering and grouping on a 33 | data set. 34 | -------------------------------------------------------------------------------- /ac1-markdown/filtering_and_grouping/summary.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | 7 | 8 | ![Graphic depicting a summary of key vocabulary from this section](figures/summary.png) 9 | -------------------------------------------------------------------------------- /ac1-markdown/filtering_and_grouping/toctree.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Filtering and Grouping 7 | ====================== 8 | 9 | Contents 10 | -------- 11 | 12 | [Introduction](introduction.md) 13 | 14 | [Filtering data](filtering_data.md) 15 | 16 | [Grouping data](grouping_data.md) 17 | 18 | [Summary](summary.md) -------------------------------------------------------------------------------- /ac1-markdown/importing_and_exporting_data/exporting_data.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Exporting Data 7 | ============== 8 | 9 | Exporting data is even easier than importing data. If you have a file 10 | sheet that is ready for export, you can just click "File \> Download", 11 | and choose which format you need to export to. The format options are: 12 | 13 | - .xlsx (compatible with Microsoft Excel) 14 | - .ods (compatible with Linux LibreOffice) 15 | - .pdf (readable on any system but non-editable) 16 | - .csv (the most common format for data storage) 17 | - .tsv (also widely used, but less so than csv) 18 | 19 | Another useful tool in Sheets allows you to publish your data online. If 20 | you click "File \> Publish to the web", you can publish your entire file 21 | or a specified sheet as a web page, or as any of the downloadable file 22 | formats above. This is a useful way to share data that will be 23 | continually updated. 24 | 25 | ![A screenshot of the pop-up box when publishing a spreadsheet from Google Sheets.](figures/publish_data.png) 26 | 27 | This image is an example of what it looks like to publish a spreadsheet 28 | from Sheets. On the left selection pane, choose how much of the file to 29 | publish. On the right selection pane, choose which file type to publish 30 | as. 31 | 32 | Always be careful to ensure no private information is present in a 33 | dataset that you publish. There may be instances where your dataset 34 | holds sensitive information. It is important to know when that is, and 35 | to understand the [laws and regulations on information 36 | privacy.](https://en.wikipedia.org/wiki/Information_privacy) On the 37 | other hand, there are plenty of publicly available datasets with 38 | important information. [Here are some of the most popular published 39 | datasets from 2018.](https://data.world/blog/top-10-datasets-2018/) 40 | 41 | For more help on publishing data from Sheets, [check out this 42 | guide](https://support.google.com/docs/answer/183965?co=GENIE.Platform%3DDesktop&hl=en) -------------------------------------------------------------------------------- /ac1-markdown/importing_and_exporting_data/figures/cereal_data.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/importing_and_exporting_data/figures/cereal_data.png -------------------------------------------------------------------------------- /ac1-markdown/importing_and_exporting_data/figures/csv_example.png: -------------------------------------------------------------------------------- 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| ======== 8 | 9 | [Importing data](importing_data.md) 10 | 11 | [Exporting data](exporting_data.md) 12 | 13 | [Summary](summary.md) -------------------------------------------------------------------------------- /ac1-markdown/introduction_to_visualizations/example_visualizations.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Example Visualizations 7 | ============================= 8 | 9 | "Hollywood's Gender Imbalance" 10 | ------------------------------ 11 | 12 | Take a look at the visualization titled "Hollywood\'s Gender Imbalance", 13 | which appears in [this article, authored by statistics-based media site 14 | FiveThirtyEight](https://projects.fivethirtyeight.com/next-bechdel/). 15 | Ask yourself the following questions. 16 | 17 | - What do you think the key point of this visualization is? 18 | - Where has the author drawn attention to, and how? 19 | - Does this visualization make the information easy to interpret? 20 | 21 | Read the article in full, then think about the following discussion 22 | questions. 23 | 24 | - Did you read every word in the article? 25 | - Did you look at every picture in the article? 26 | - Did the visualization make this information easier to interpret than 27 | the text did? 28 | 29 | "What if only non-white people voted?" 30 | -------------------------------------- 31 | 32 | FiveThirtyEight also posted an article that asks: [what if only certain 33 | subsets of US citizens 34 | voted?](https://fivethirtyeight.com/features/what-if-only-men-voted-only-women-only-nonwhite-voters/) 35 | *Before* you read this article, just scroll through the article and look 36 | only at the maps. Then, read all of the text *without* looking at any of 37 | the maps. 38 | 39 | - Which reading of the article conveyed more information? 40 | - Which reading of the article took more time? 41 | - Which reading of the article was more enjoyable? 42 | 43 | ### Short Answer 44 | 45 | - How do you think researchers got statistics on how different groups 46 | voted? 47 | 48 | -------------------------------------------------------------------------------- /ac1-markdown/introduction_to_visualizations/figures/bar_chart_example.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/introduction_to_visualizations/figures/bar_chart_example.png -------------------------------------------------------------------------------- /ac1-markdown/introduction_to_visualizations/figures/color_blind.png: 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Colors and patterns can 10 | be easier to interpret than words and numbers. Have you ever read an 11 | article that does not include some form of picture, or graphic, or map? 12 | Visualizations make data easy to access, make articles easy to read, and 13 | make findings easy to interpret. 14 | 15 | **A data visualization is any visual representation of data.** Examples 16 | include: 17 | 18 | - Tables 19 | - Line graphs 20 | - Maps 21 | - Pie charts 22 | - Infographics 23 | 24 | In this chapter, you will learn more about when to use different 25 | visualizations and how to ensure that they effectively communicate data 26 | to your audience. To start, take a look at the visualizations below. 27 | While reviewing them, keep in mind what you like about them and what 28 | elements on them guide your understanding of their meaning. 29 | 30 | Pie Chart 31 | --------- 32 | 33 | ![An example pie chart visualization.](figures/example_pie_chart.png) 34 | 35 | This pie chart example shows the proportion of the backgrounds for the 36 | most influential artists of their time from different countries. 37 | 38 | Table 39 | ----- 40 | 41 | ![An example table visualization.](figures/table_data_example.png) 42 | 43 | This table holds standard information about people. Each column contains 44 | data for a different category. 45 | 46 | Bar Chart 47 | --------- 48 | 49 | ![An example bar chart visualization.](figures/bar_chart_example.png) 50 | 51 | This figure holds information about the amount of trips and average fare 52 | depending on the duration of taxi rides in Chicago. 53 | -------------------------------------------------------------------------------- /ac1-markdown/introduction_to_visualizations/summary.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | 7 | 8 | ![A line graph comparing number of likes over time of two posts.](figures/summary.png) 9 | -------------------------------------------------------------------------------- /ac1-markdown/introduction_to_visualizations/toctree.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Introduction To Visualizations 7 | ============================== 8 | 9 | Contents 10 | -------- 11 | 12 | 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In this section, you will learn more ways to 11 | manipulate data in Sheets by creating pivot tables, and joining 12 | different pieces of data into one table. With these tools, you can more 13 | easily see summary statistics of your data and do further data analysis. 14 | -------------------------------------------------------------------------------- /ac1-markdown/manipulating_data/summary.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | 7 | 8 | ![Graphic summarizing key concepts of manipulating data in Sheets.](figures/manipulating_data_summary.png) 9 | -------------------------------------------------------------------------------- /ac1-markdown/manipulating_data/toctree.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Contents 7 | ======== 8 | 9 | [Introduction](introduction.md) 10 | 11 | [Pivot tables](pivot_tables.md) 12 | 13 | [Joining data](joining_data.md) 14 | 15 | [Summary](summary.md) -------------------------------------------------------------------------------- /ac1-markdown/module_b_preface.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Module B Preface 7 | ================ 8 | 9 | In the previous module, you learned techniques to analyze data in Google 10 | Sheets. Now, it\'s time to learn how to analyze even larger datasets. 11 | This is especially important when you are trying to draw larger 12 | conclusions. One of the most fundamental use cases for statistics is 13 | investigating the relationship between multiple variables. When reading 14 | stories in the media, there is often discussion about links between two 15 | or more variables. For example: 16 | 17 | - [Does eating more chocolate increase your life 18 | expectancy?](https://www.unilad.co.uk/food/eating-chocolate-helps-you-live-longer/) 19 | - [Do vaccines increase the chance of 20 | autism?](https://www.cdc.gov/vaccinesafety/concerns/autism.html) 21 | - [Does gun ownership rate increase gun 22 | fatalities?](https://www.nytimes.com/2019/07/22/us/gun-ownership-violence-statistics.html) 23 | - [Does home field advantage in sports really 24 | exist?](https://fivethirtyeight.com/features/the-nfls-home-field-advantage-is-real-but-why/) 25 | - [Does reading Harry Potter reduce a person's 26 | prejudice?](https://www.independent.co.uk/arts-entertainment/books/news/harry-potter-jk-rowling-reduce-prejudice-study-journal-applied-psychology-a7414706.html) 27 | 28 | However, for every article with a statistical study that argues for one 29 | thing, there is usually at least one for the other side. Since there is 30 | so much news from so many diverse sources, it has become increasingly 31 | important to decipher which studies are trustworthy, what statistics are 32 | reliable, and what findings are legitimate. 33 | 34 | In the next few chapters, you will learn more about analyzing the 35 | relationship between variables. This will help you investigate the 36 | relationship between pairs of variables for your own analysis, as well 37 | as critically assess the statistical findings you read about in the 38 | media. -------------------------------------------------------------------------------- /ac1-markdown/module_c_preface.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Module C Preface 7 | ================ 8 | 9 | A lot of the data that we interact with today is stored in databases. 10 | You can think of a database as a group of tables. These tables have rows 11 | and columns just like spreadsheets. Some examples of data that can be 12 | stored in databases are listed below. 13 | 14 | - Student records, including grades, at a school 15 | - Posts and friends in your favorite social network 16 | - News stories on a newspaper's website 17 | - Your contacts list on your mobile phone 18 | - All images that make up Google Maps 19 | 20 | All these bits of information are stored in various kinds of databases. 21 | Some of these are stored in a relational database, which is a database 22 | that stores data points that are related to one another in some way. 23 | These databases are available as open source tools like Postgresql, 24 | MySQL and SQLite, as well as commercial databases such as [Google 25 | BigQuery](https://cloud.google.com/bigquery/), 26 | [Oracle](https://www.oracle.com/database/technologies/), [Microsoft SQL 27 | Server](https://azure.microsoft.com/en-us/services/virtual-machines/sql-server/), 28 | or [Amazon Aurora](https://aws.amazon.com/rds/aurora/). Others are 29 | stored in proprietary systems like Google's 30 | [BigTable](https://en.wikipedia.org/wiki/Bigtable) or Facebook's 31 | [Haystack Object 32 | Store](https://code.fb.com/core-data/needle-in-a-haystack-efficient-storage-of-billions-of-photos/). 33 | 34 | While the mechanism and content of the database may vary, there is a 35 | common language used to extract data: this language is called Structured 36 | Query Language (SQL, pronounced "sequel"). This module will teach you 37 | how you can use SQL to analyze data in a database. 38 | -------------------------------------------------------------------------------- /ac1-markdown/projects/toctree.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Projects 7 | ======== 8 | 9 | [Module A](module_a.md) 10 | 11 | [Module B](module_b.md) 12 | 13 | [Module C](module_c.md) 14 | -------------------------------------------------------------------------------- /ac1-markdown/regression_and_line_of_best_fit/creating_line_of_best_fit.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Creating a Line of Best Fit 7 | =========================== 8 | 9 | In order to analyze a line of best fit for a scatter plot, you will 10 | first need to make one. You can do this in Sheets through an option in 11 | the chart editor. After making a scatter plot, you can add a line of 12 | best fit by opening the chart editor by clicking the three dots in the 13 | top right corner. 14 | 15 | ![Screenshot showing how to edit a chart by clicking the three dots in the top right corner.](figures/edit_chart.png) 16 | 17 | Once the chart editor is open, make sure customize is selected. Under 18 | "Series", there is a checkbox to add a trendline. You can change the 19 | color and thickness of the line, display the R2 value, (this is the 20 | same as the coefficient of determination), and display the equation of 21 | the line. 22 | 23 | ![Screenshot showing how to add trendline.](figures/add_trendline.png) 24 | 25 | Once you have added a trendline, it will appear on your graph. 26 | 27 | ![Scatter plot with a trendline.](figures/average_sat_score_completion_rate.png) 28 | 29 | Now that there is a trendline and equation of a line on the graph, you 30 | can use this information to analyze data and predict results given your 31 | data. In particular you can use the slope and y-intercept. Don\'t worry 32 | if you don\'t remember how to find this information from the equation of 33 | a line, the next section will guide you through this. 34 | -------------------------------------------------------------------------------- /ac1-markdown/regression_and_line_of_best_fit/equation_of_a_line_refresher.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Equation of a Line (Refresher) 7 | ============================== 8 | 9 | ![Slope intercept form: y equals m times x plus b.](figures/equation_of_a_line.png) 10 | 11 | All line equations in this text will be presented in the form *y = mx + 12 | b*, where *m* is the slope and *b* is the y-intercept. This is also 13 | called slope-intercept form. The **y-intercept** is the y-value at the 14 | point where the line crosses the y-axis. The 15 | [slope](interpreting_slope.md) gives the 16 | steepness of the line, and can be positive, negative, or zero. 17 | Slope-intercept form is a method to better understand the relationship 18 | between the two variables *x* and *y*. 19 | 20 | ![A graph of the equation y equals negative one third times x plus five and the slope is negative.](figures/negative_slope.png) 21 | 22 | This figure depicts an equation of a line that has a y-intercept of 5 23 | and a negative slope. 24 | 25 | ![A graph of the equation of y equals 2 times x plus one.](figures/positive_slope.png) 26 | 27 | The equation of the line in the above figure has a y-intercept of 1 and 28 | a positive slope. 29 | 30 | For additional review on slope-intercept form you can also watch out 31 | [this 32 | video](https://www.khanacademy.org/math/algebra/x2f8bb11595b61c86:forms-of-linear-equations/x2f8bb11595b61c86:intro-to-slope-intercept-form/v/slope-intercept-form). 33 | 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The 11 | closer the coefficient of determination (or R2 value) is to 1, and 12 | the closer the points of the scatter plot are to a straight line, the 13 | more reliable your predictions will be. But what does this line actually 14 | mean and how can it help you make predictions? 15 | 16 | This line is called the **line of best fit**, or a **regression line**. 17 | This line can be used to predict information about values that you may 18 | not have data for. A line of best fit for a scatter plot could look 19 | something like the following. 20 | 21 | ![Scatter plot with a line of best fit.](figures/average_sat_score_completion_rate.png) 22 | 23 | In this section, you'll learn how to create a line of best fit in 24 | Sheets, use the equation of the line of best fit to make predictions, 25 | and explain how changes in one variable may impact the other. Here are 26 | some questions a line of best fit helps to answer. 27 | 28 | - If a school has an average SAT score of 1200, what is its predicted 29 | completion rate? 30 | - If two schools have a difference of 100 points in average SAT score, 31 | will their graduates make different salaries after graduation? If 32 | so, by how much? 33 | - How does the percentage of students receiving federal loans impact 34 | completion rates? 35 | 36 | You will work through some examples throughout this section to find 37 | answers to these questions. 38 | -------------------------------------------------------------------------------- /ac1-markdown/regression_and_line_of_best_fit/summary.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | 7 | 8 | ![Graphic summarizing key concepts of regression and line of best fit.](figures/regression_summary.png) -------------------------------------------------------------------------------- /ac1-markdown/regression_and_line_of_best_fit/toctree.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Contents 7 | ======== 8 | 9 | [Introduction](introduction.md) 10 | 11 | [Creating line of best fit](creating_line_of_best_fit.md) 12 | 13 | [Equation of a line refresher](equation_of_a_line_refresher.md) 14 | 15 | [Interpreting slope](interpreting_slope.md) 16 | 17 | [Making predictions with the regression line](making_predictions_with_the_regression_line.md) 18 | 19 | [Outliers](outliers.md) 20 | 21 | [Nonlinear regression](nonlinear_regression.md) 22 | 23 | [Summary](summary.md) -------------------------------------------------------------------------------- /ac1-markdown/scatter_plots_and_correlation/figures/avg_if.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/scatter_plots_and_correlation/figures/avg_if.png -------------------------------------------------------------------------------- /ac1-markdown/scatter_plots_and_correlation/figures/avg_temp_region_jan.png: -------------------------------------------------------------------------------- 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However, 11 | sometimes these visualizations are not the most intuitive for looking at 12 | individual pieces of a larger data set. This is where scatter plots come 13 | in. Scatter plots are a type of data visualization that show the 14 | relationship between two quantitative variables. An example of a scatter 15 | plot is shown below. As you can see in the screenshot, each data point 16 | is plotted individually onto a graph. By organizing data this way, it 17 | becomes easier to understand trends in larger data sets. 18 | 19 | ![An example of a scatter plot](figures/example_scatterplot.png) 20 | 21 | In this section, you will learn how to create, read, and analyze scatter 22 | plots. You will first begin by working through an example to see why 23 | scatter plots are useful. 24 | -------------------------------------------------------------------------------- /ac1-markdown/scatter_plots_and_correlation/summary.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | 7 | 8 | ![A summary of the scatterplots section.](figures/summary.png) 9 | -------------------------------------------------------------------------------- /ac1-markdown/scatter_plots_and_correlation/toctree.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Contents 7 | ======== 8 | 9 | [Introduction](introduction.md) 10 | 11 | [Motivating scatterplots](motivating_scatterplots.md) 12 | 13 | [Scatter plots](scatter_plots.md) 14 | 15 | [Creating a scatter plot in Sheets](creating_a_scatter_plot_in_sheets.md) 16 | 17 | [Describing scatter plots](describing_scatter_plots.md) 18 | 19 | [Correlation](correlation.md) 20 | 21 | [Correlation and college data](correlation_and_college_data.md) 22 | 23 | [Correlation versus causation](correlation_versus_causation.md) 24 | 25 | [Correlation and filtering](correlation_and_filtering.md) 26 | 27 | [Summary](summary.md) -------------------------------------------------------------------------------- /ac1-markdown/sheets_basics/errors.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Errors 7 | ====== 8 | 9 | If Sheets cannot interpret your formula or your formula cannot be 10 | computed, you will see an **error**. An example of this is below. Cell 11 | A1 is the formula, `B1` is the result. Note the red line under `A1` 12 | indicating Sheets will throw an error here. The box entitled `Error` 13 | tells you why Sheets could not compute the formula. 14 | 15 | ![Cell with 1 divided by 0 with error box that says \"Function DIVIDE 16 | parameter 2 cannot be zero.\"](figures/sheets_error.png) 17 | 18 | There are [several types of 19 | errors](https://infoinspired.com/google-docs/spreadsheet/different-error-types-in-google-sheets/), 20 | and this section does not cover them in depth. Throughout this course, 21 | you will undoubtedly come across such errors, and that is absolutely 22 | normal. Not encountering errors would indeed be suspicious! In general, 23 | there is no foolproof way to debug these errors, but some useful tips 24 | are below. 25 | 26 | 1. **Look at the error message.** In the above example, "Function 27 | DIVIDE parameter 2 cannot be zero" is telling you that the second 28 | value (the value after the division symbol "/") cannot be zero, 29 | since dividing by zero is infinite or undefined mathematically. 30 | 2. **If you are using a function, know the inputs.** [This 31 | table](https://support.google.com/docs/table/25273), written by 32 | Google, lists all functions and how to set the inputs. The table is 33 | ordered by "type", so you can find common mathematical functions 34 | with the type "Math". 35 | 3. **Try Googling your error.** If you are facing an error, chances are 36 | several people have seen it before. Try searching for the error 37 | message or the broken formula online. Sites like [Google 38 | Support](http://support.google.com) and 39 | [StackOverflow](http://stackoverflow.com) have helped millions. 40 | 4. **Practice makes perfect.** No matter what you do, you will see 41 | errors. Debugging errors is a big part of coding, but the more you 42 | practice, the fewer errors you will see. 43 | -------------------------------------------------------------------------------- /ac1-markdown/sheets_basics/figures/chocolate_cake_amounts_for_custom_servings.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/sheets_basics/figures/chocolate_cake_amounts_for_custom_servings.png -------------------------------------------------------------------------------- /ac1-markdown/sheets_basics/figures/chocolate_cake_custom_servings.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/sheets_basics/figures/chocolate_cake_custom_servings.png -------------------------------------------------------------------------------- /ac1-markdown/sheets_basics/figures/chocolate_cake_flour_for_18_servings.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/sheets_basics/figures/chocolate_cake_flour_for_18_servings.png -------------------------------------------------------------------------------- /ac1-markdown/sheets_basics/figures/chocolate_cake_flour_for_custom_servings.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/sheets_basics/figures/chocolate_cake_flour_for_custom_servings.png -------------------------------------------------------------------------------- /ac1-markdown/sheets_basics/figures/chocolate_cake_relative_referencing_not_working.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/sheets_basics/figures/chocolate_cake_relative_referencing_not_working.png -------------------------------------------------------------------------------- /ac1-markdown/sheets_basics/figures/painters_example_sheets.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/sheets_basics/figures/painters_example_sheets.png -------------------------------------------------------------------------------- /ac1-markdown/sheets_basics/figures/sheet_example.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/sheets_basics/figures/sheet_example.png -------------------------------------------------------------------------------- /ac1-markdown/sheets_basics/figures/sheets_error.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/sheets_basics/figures/sheets_error.png -------------------------------------------------------------------------------- /ac1-markdown/sheets_basics/figures/sheets_keyword_definitions.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/sheets_basics/figures/sheets_keyword_definitions.png -------------------------------------------------------------------------------- /ac1-markdown/sheets_basics/figures/sheets_summary.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/sheets_basics/figures/sheets_summary.png -------------------------------------------------------------------------------- /ac1-markdown/sheets_basics/introduction.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Introduction 7 | ============ 8 | 9 | Spreadsheets are a very powerful and widely-used tool. Spreadsheet softwares can 10 | generate graphs, do calculations extremely quickly, and even predict the future 11 | using statistics! 12 | This section introduces you to the basics of spreadsheets, and walks through a 13 | few illustrative examples. 14 | 15 | There are multiple spreadsheet softwares and the one we will focus on in this 16 | textbook is Google Sheets. While functionality may differ slightly across 17 | platforms, the core concepts and syntaxes are the same. In this course, whenever 18 | sheets are mentioned, it is in reference to Google Sheets, which is pictured 19 | below with example [student data](https://docs.google.com/spreadsheets/d/1SbhCo8ZjEfFmBGwE7TLdsq-mxvMQa3hOmL5DMWF2ZTc/edit?usp=sharing). 20 | 21 | ![Spreadsheet with example student data of name, height, hair color.](figures/sheet_example.png) 22 | -------------------------------------------------------------------------------- /ac1-markdown/sheets_basics/summary.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | 7 | 8 | ![Graphic summarizing key concepts of basic descriptive statistics.](figures/sheets_summary.png) 9 | -------------------------------------------------------------------------------- /ac1-markdown/sheets_basics/toctree.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Sheets Basics 7 | ============= 8 | 9 | Contents 10 | -------- 11 | 12 | [Introduction](introduction.md) 13 | 14 | [What is a sheet](what_is_a_sheet.md) 15 | 16 | [What is a formula](what_is_a_formula.md) 17 | 18 | [Errors](errors.md) 19 | 20 | [Summary](summary.md) -------------------------------------------------------------------------------- /ac1-markdown/sql/figures/bike_dataset_columns.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/sql/figures/bike_dataset_columns.png -------------------------------------------------------------------------------- /ac1-markdown/sql/figures/summary.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1-markdown/sql/figures/summary.png -------------------------------------------------------------------------------- /ac1-markdown/sql/filtering.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Filtering 7 | ========= 8 | 9 | In this section, you will learn how to filter data in SQL. Previously, 10 | you learned how to filter data in Sheets. Filtering data is to look at 11 | only a subset of rows, based on some column condition. For example, if 12 | you have a database containing information for all citizens of the USA, 13 | a filter could be applied to look only at residents of Texas. You have 14 | already seen 15 | [how to apply filters in Sheets](../filtering_and_grouping/filtering_data.md). 16 | 17 | Filtering data in SQL is as simple as using the `WHERE` keyword. You can 18 | append `WHERE column_condition` to any SQL query, and the result will be 19 | filtered only to rows that satisfy the column condition. For example, 20 | you might want to look only at bike trips which are at least one hour 21 | (3600 seconds). 22 | 23 | ``` {sql} 24 | SELECT 25 | member_type, start_date, duration 26 | FROM 27 | trip_data 28 | WHERE 29 | duration >= 3600 30 | LIMIT 31 | 10 32 | ``` 33 | 34 | It is also possible to filter by multiple criteria. For example to look 35 | at bike trips which are 60 minutes or more and the `member_type` is 36 | `MEMBER`, the query would be as below. 37 | 38 | ``` {sql} 39 | SELECT 40 | member_type, start_date, duration 41 | FROM 42 | trip_data 43 | WHERE 44 | duration >= 3600 AND member_type = 'Member' 45 | LIMIT 46 | 10 47 | ``` 48 | 49 | ### Fill in the blank 50 | 51 | 1. Write a query to find the ending station and duration of all of trips by 52 | bike number W00153 that lasted over 8 hours. 53 | 54 | 2. How many trips started and ended at station 31111? 55 | 56 |
57 | Answers 58 |
59 | 60 | 1. 31606, 40791, 31703, 40820 61 | 62 | 2. 92 63 | 64 |
65 | -------------------------------------------------------------------------------- /ac1-markdown/sql/how_to_run_sql.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | How to Run SQL Outside of This Textbook 7 | ======================================= 8 | 9 | In this section, you will learn some basic SQL commands to analyze large 10 | datasets. In the interactive version of this textbook, there is a SQL 11 | interpreter. However, when using SQL outside of the textbook, including 12 | in your project, you will need to run SQL somewhere else. In order to do 13 | this, there are many options. If you are using SQL for just this course, 14 | you can use an online interpreter, such as this one. When importing a 15 | .db file directly, select the File drop drown from the top left of the 16 | webpage and select Open DB to use your .db file. 17 | 18 | - [SQL Online Interpreter](https://sqliteonline.com/) 19 | 20 | Ultimately, if you plan on using SQL for more robust purposes, you will 21 | want to run SQL queries on your own machine. To do this, you will need 22 | to download a Database Engine and set up a Database Client. There are 23 | many options for database engines you can use. Some of the most popular 24 | ones are listed below. Each link takes you to the setup documentation 25 | for the database engine. Pick one that feels right to you and follow the 26 | instructions. If you would like more explanation as to which database 27 | engine you should use, read about a [comparison of relational database 28 | management 29 | systems.](https://www.digitalocean.com/community/tutorials/sqlite-vs-mysql-vs-postgresql-a-comparison-of-relational-database-management-systems) 30 | 31 | - [SQLite](https://www.sqlite.org/quickstart.html) 32 | - [MySQL](https://dev.mysql.com/doc/mysql-getting-started/en/) 33 | - [PostgreSQL](https://www.postgresql.org/docs/10/tutorial-start.html) 34 | - [BigQuery](https://cloud.google.com/bigquery/docs) 35 | -------------------------------------------------------------------------------- /ac1-markdown/sql/introduction.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | Introduction 7 | ============ 8 | 9 | As mentioned in the preface, SQL (which stands for Structured Query 10 | Language) is a programming language that is used to get, store, and 11 | change information in a database. SQL is one of the most widely used 12 | programming languages today, and can be used in any field where there is 13 | data. 14 | 15 | You may be wondering when you would need to use SQL since you already 16 | know how to use Sheets. SQL does many of the things that you have 17 | learned in the previous sections, but it also does them on a much larger 18 | scale. Imagine a spreadsheet with one billion rows! 19 | 20 | You can use SQL to analyze anything from stock market prices to patient 21 | data at a major hospital. If you have a database with any kind of data, 22 | you can use SQL to store and analyze it. In addition, SQL allows you to 23 | reorganize data across different datasets. This chapter will teach you 24 | how to use SQL to automate data analysis so that you can effectively 25 | navigate large datasets that might be cumbersome to navigate by hand. 26 | -------------------------------------------------------------------------------- /ac1-markdown/sql/summary.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | 7 | 8 | ![A summary of the sql section.](figures/summary.png) 9 | -------------------------------------------------------------------------------- /ac1-markdown/sql/toctree.md: -------------------------------------------------------------------------------- 1 | 5 | 6 | SQL 7 | === 8 | 9 | Contents 10 | -------- 11 | 12 | [Introduction](introduction.md) 13 | 14 | [How to run SQL](how_to_run_sql.md) 15 | 16 | [Selecting](selecting.md) 17 | 18 | [Filtering](filtering.md) 19 | 20 | [Sorting](sorting.md) 21 | 22 | [Aggregating](aggregating.md) 23 | 24 | [Ifs and cases](ifs_and_cases.md) 25 | 26 | 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Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Introduction 8 | ============ 9 | 10 | Statistics are everywhere: in news articles, sports, government reports, 11 | research papers, just to name a few. Using statistics is so popular because they 12 | provide evidence and credibility to claims. 13 | 14 | Here are just a few examples of how a variety of fields use statistics: 15 | 16 | - Journalists use data to substantiate their reporting. 17 | - Political leaders use data to inform their decisions. 18 | - Sports teams and businesses lean heavily on statistical algorithms for their 19 | actions. 20 | - Psychologists use statistics to give meaning to the data they collected. 21 | 22 | As much as statistics are used, statistics are also frequently misused. One of 23 | the most important mediums in which statistics are often misused is the news. 24 | Since the claims made in the news often impact the world around you, it’s 25 | important for you to be able to critically assess those statistics. 26 | 27 | Consider the following two sentences: 28 | 29 | 1. “Americans are spending a lot of time watching TV.” 30 | 2. “Adult Americans are spending on average five hours and four minutes 31 | watching TV per day.” 32 | 33 | Although both sentences make the same point, the statistic used in the second 34 | sentence makes the claim much more specific than the first. The specificity 35 | provided by statistics is a powerful tool that allows you to support your own 36 | claims or drive your own decision-making in any field of work or study. 37 | -------------------------------------------------------------------------------- /ac1/_sources/basic_descriptive_statistics/summary.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | .. Location of summary document: shorturl.at/mrLNV 7 | 8 | Summary 9 | ======= 10 | 11 | .. image:: figures/statistics_summary.png 12 | :align: center 13 | :alt: Graphic summarizing key concepts of basic descriptive statistics. 14 | -------------------------------------------------------------------------------- /ac1/_sources/basic_descriptive_statistics/toctree.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Basic Descriptive Statistics 8 | ============================ 9 | 10 | .. toctree:: 11 | :caption: Contents 12 | :maxdepth: 2 13 | 14 | introduction.rst 15 | what_is_a_statistic.rst 16 | variables.rst 17 | count_and_sum.rst 18 | minimum_and_maximum.rst 19 | measures_of_center.rst 20 | outliers_and_skew.rst 21 | measures_of_spread.rst 22 | summary.rst 23 | -------------------------------------------------------------------------------- /ac1/_sources/basic_descriptive_statistics/what_is_a_statistic.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | What Is A Statistic? 8 | ==================== 9 | 10 | Many people discuss statistics, but not everyone knows what a statistic actually 11 | is. 12 | 13 | 14 | .. admonition:: Statistic Definition 15 | 16 | **A statistic is a fact of the data.** A statistic is any piece of 17 | information you can get from a set of data. 18 | 19 | 20 | For example, suppose you have a dataset containing the heights of all students 21 | in this class. 22 | 23 | 24 | .. image:: figures/height_statistic.png 25 | :align: center 26 | 27 | 28 | The following are all statistics from that dataset. 29 | 30 | - The shortest height is 146cm. 31 | - The tallest height is 192cm. 32 | - There are 19 students in this class. 33 | - The average height is 166.16cm. 34 | - The sum of all heights in the class is 3157cm. 35 | - Half the maximum height is 96cm. 36 | 37 | Some statistics are more common and useful than others. For example, knowing 38 | the average height will likely be more useful in real life than knowing the sum 39 | of all heights. This chapter will guide you through the most common descriptive 40 | statistics. 41 | 42 | Suppose you have a dataset on how far students travel to get to school. 43 | 44 | .. image:: figures/distance_statistic.png 45 | :align: center 46 | 47 | .. shortanswer:: students_travel_statistics 48 | 49 | What are some important statistics of the dataset above? 50 | 51 | -------------------------------------------------------------------------------- /ac1/_sources/filtering_and_grouping/figures/create_a_filter.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/filtering_and_grouping/figures/create_a_filter.png -------------------------------------------------------------------------------- /ac1/_sources/filtering_and_grouping/figures/filter_french_painters.png: -------------------------------------------------------------------------------- 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Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Introduction 8 | ============ 9 | 10 | Now that Sheets is more familiar and you know how it can hold data, you will 11 | learn how Sheets can also be used to organize that data. Sheets has functions 12 | that allow you to **filter** as well as **group** data. For example, if you had 13 | the table below you could use filtering and grouping to more easily display 14 | certain data. 15 | 16 | 17 | .. image:: figures/table_data.png 18 | :align: center 19 | :alt: Table containing basic data for 23 people. 20 | 21 | 22 | Above is a table with some standard information collected from a group of 23 23 | people. This data is fictional. Below is the same data from this table after 24 | filtering and grouping are separately applied. 25 | 26 | .. image:: figures/table_filter_example.png 27 | :align: center 28 | :alt: The same table after applying a filter. 29 | 30 | 31 | This is an example of **filtering** the data to only see rows of people whose 32 | city is Los Angeles. 33 | 34 | 35 | .. image:: figures/table_group_example.png 36 | :align: center 37 | :alt: The same table after applying grouping. 38 | 39 | This is an example of **grouping** the data to count the number of people in 40 | this dataset who are from Los Angeles. 41 | 42 | Don't worry if this is confusing. These examples are meant to help you become 43 | more familiar with applications of filtering and grouping on a data set. 44 | -------------------------------------------------------------------------------- /ac1/_sources/filtering_and_grouping/summary.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | .. Location of summary document: shorturl.at/mrLNV 7 | 8 | Summary 9 | ======= 10 | 11 | .. image:: figures/filtering_summary.png 12 | :align: center 13 | -------------------------------------------------------------------------------- /ac1/_sources/filtering_and_grouping/toctree.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Filtering and Grouping 8 | ====================== 9 | 10 | .. toctree:: 11 | :caption: Contents 12 | :maxdepth: 2 13 | 14 | introduction.rst 15 | filtering_data.rst 16 | grouping_data.rst 17 | summary.rst 18 | -------------------------------------------------------------------------------- /ac1/_sources/importing_and_exporting_data/figures/cereal_data.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/importing_and_exporting_data/figures/cereal_data.png -------------------------------------------------------------------------------- /ac1/_sources/importing_and_exporting_data/figures/csv_example.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/importing_and_exporting_data/figures/csv_example.png -------------------------------------------------------------------------------- /ac1/_sources/importing_and_exporting_data/figures/import_example.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/importing_and_exporting_data/figures/import_example.png -------------------------------------------------------------------------------- /ac1/_sources/importing_and_exporting_data/figures/importing_summary.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/importing_and_exporting_data/figures/importing_summary.png -------------------------------------------------------------------------------- /ac1/_sources/importing_and_exporting_data/figures/publish_data.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/importing_and_exporting_data/figures/publish_data.png -------------------------------------------------------------------------------- /ac1/_sources/importing_and_exporting_data/figures/separatortype_example.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/importing_and_exporting_data/figures/separatortype_example.png -------------------------------------------------------------------------------- /ac1/_sources/importing_and_exporting_data/figures/ssv_example.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/importing_and_exporting_data/figures/ssv_example.png -------------------------------------------------------------------------------- /ac1/_sources/importing_and_exporting_data/figures/tsv_example.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/importing_and_exporting_data/figures/tsv_example.png -------------------------------------------------------------------------------- /ac1/_sources/importing_and_exporting_data/figures/upload_example.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/importing_and_exporting_data/figures/upload_example.png -------------------------------------------------------------------------------- /ac1/_sources/importing_and_exporting_data/summary.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | .. Link to summary document: shorturl.at/mrLNV 7 | 8 | Summary 9 | ======= 10 | 11 | .. image:: figures/importing_summary.png 12 | :align: center 13 | :alt: Graphic summarizing key concepts of importing and exporting files. 14 | -------------------------------------------------------------------------------- /ac1/_sources/importing_and_exporting_data/toctree.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Importing and Exporting Data 8 | ============================ 9 | 10 | .. toctree:: 11 | :caption: Contents 12 | :maxdepth: 2 13 | 14 | importing_data.rst 15 | exporting_data.rst 16 | summary.rst 17 | -------------------------------------------------------------------------------- /ac1/_sources/index.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Applied Computing 1 Textbook 8 | ============================ 9 | 10 | .. Here is were you specify the content and order of your new book. 11 | 12 | .. Each section heading (e.g. "SECTION 1: A Random Section") will be 13 | a heading in the table of contents. Source files that should be 14 | generated and included in that section should be placed on individual 15 | lines, with one line separating the first source filename and the 16 | :maxdepth: line. 17 | 18 | .. Sources can also be included from subfolders of this directory. 19 | (e.g. "DataStructures/queues.rst"). 20 | 21 | Contents 22 | -------- 23 | 24 | .. toctree:: 25 | :maxdepth: 1 26 | 27 | module_a_preface.rst 28 | 29 | .. toctree:: 30 | :maxdepth: 2 31 | 32 | introduction_to_visualizations/toctree.rst 33 | sheets_basics/toctree.rst 34 | basic_descriptive_statistics/toctree.rst 35 | filtering_and_grouping/toctree.rst 36 | 37 | .. toctree:: 38 | :maxdepth: 1 39 | 40 | module_b_preface.rst 41 | 42 | .. toctree:: 43 | :maxdepth: 2 44 | 45 | importing_and_exporting_data/toctree.rst 46 | scatter_plots_and_correlation/toctree.rst 47 | regression_and_line_of_best_fit/toctree.rst 48 | manipulating_data/toctree.rst 49 | 50 | .. toctree:: 51 | :maxdepth: 1 52 | 53 | module_c_preface.rst 54 | 55 | .. toctree:: 56 | :maxdepth: 2 57 | 58 | sql/toctree.rst 59 | 60 | .. toctree:: 61 | :maxdepth: 2 62 | 63 | projects/toctree.rst 64 | -------------------------------------------------------------------------------- /ac1/_sources/introduction_to_visualizations/example_visualizations.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Example Visualizations 8 | ====================== 9 | 10 | “Hollywood's Gender Imbalance” 11 | ------------------------------ 12 | 13 | Take a look at the visualization titled “Hollywood's Gender Imbalance”, which 14 | appears in `this article, authored by statistics-based media site 15 | FiveThirtyEight`_. Ask yourself the following questions. 16 | 17 | - What do you think the key point of this visualization is? 18 | - Where has the author drawn attention to, and how? 19 | - Does this visualization make the information easy to interpret? 20 | 21 | Read the article in full, then think about the following discussion questions. 22 | 23 | - Did you read every word in the article? 24 | - Did you look at every picture in the article? 25 | - Did the visualization make this information easier to interpret than the 26 | text did? 27 | 28 | 29 | “What if only non-white people voted?” 30 | -------------------------------------- 31 | 32 | FiveThirtyEight also posted an article that asks: `what if only certain subsets 33 | of US citizens voted?`_ *Before* you read this article, just scroll through the 34 | article and look only at the maps. Then, read all of the text *without* looking 35 | at any of the maps. 36 | 37 | - Which reading of the article conveyed more information? 38 | - Which reading of the article took more time? 39 | - Which reading of the article was more enjoyable? 40 | 41 | 42 | .. shortanswer:: 538_information_collection 43 | 44 | How do you think researchers got statistics on how different groups voted? 45 | 46 | 47 | .. _this article, authored by statistics-based media site FiveThirtyEight: https://projects.fivethirtyeight.com/next-bechdel/ 48 | .. _what if only certain subsets of US citizens voted?: https://fivethirtyeight.com/features/what-if-only-men-voted-only-women-only-nonwhite-voters/ 49 | -------------------------------------------------------------------------------- /ac1/_sources/introduction_to_visualizations/figures/bar_chart_example.png: -------------------------------------------------------------------------------- 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Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Introduction 8 | ============ 9 | 10 | People often find it easier to learn visually. Colors and patterns can be easier 11 | to interpret than words and numbers. Have you ever read an article that does not 12 | include some form of picture, or graphic, or map? Visualizations make data easy 13 | to access, make articles easy to read, and make findings easy to interpret. 14 | 15 | **A data visualization is any visual representation of data.** Examples include: 16 | 17 | - Tables 18 | - Line graphs 19 | - Maps 20 | - Pie charts 21 | - Infographics 22 | 23 | In this chapter, you will learn more about when to use different visualizations 24 | and how to ensure that they effectively communicate data to your audience. 25 | To start, take a look at the visualizations below. While reviewing them, 26 | keep in mind what you like about them and what elements on them guide your 27 | understanding of their meaning. 28 | 29 | 30 | Pie Chart 31 | ========= 32 | 33 | .. image:: figures/example_pie_chart.png 34 | :align: center 35 | :alt: An example pie chart visualization. 36 | 37 | This pie chart example shows the proportion of the backgrounds for the most 38 | influential artists of their time from different countries. 39 | 40 | Table 41 | ===== 42 | 43 | .. image:: figures/table_data_example.png 44 | :align: center 45 | :alt: An example table visualization. 46 | 47 | This table holds standard information about people. Each column contains data 48 | for a different category. 49 | 50 | Bar Chart 51 | ========= 52 | 53 | .. image:: figures/bar_chart_example.png 54 | :align: center 55 | :alt: An example bar chart visualization. 56 | 57 | This figure holds information about the amount of trips and average fare 58 | depending on the duration of taxi rides in Chicago. 59 | -------------------------------------------------------------------------------- /ac1/_sources/introduction_to_visualizations/summary.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | .. Location of summary document: shorturl.at/mrLNV 7 | 8 | Summary 9 | ======= 10 | 11 | .. image:: figures/visualizations_summary.png 12 | :align: center 13 | :alt: Summary for the visualizations section. 14 | -------------------------------------------------------------------------------- /ac1/_sources/introduction_to_visualizations/toctree.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. 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Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Introduction 8 | ============ 9 | 10 | Previously, you saw how you can use Sheets to manipulate data by filtering and 11 | grouping. In this section, you will learn more ways to manipulate data in 12 | Sheets by creating pivot tables, and joining different pieces of data into one 13 | table. With these tools, you can more easily see summary statistics of your 14 | data and do further data analysis. 15 | -------------------------------------------------------------------------------- /ac1/_sources/manipulating_data/summary.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | .. Link to summary document: shorturl.at/mrLNV 7 | 8 | Summary 9 | ======= 10 | 11 | .. image:: figures/manipulating_summary.png 12 | :align: center 13 | :alt: Graphic summarizing key concepts of manipulating data in Sheets. 14 | -------------------------------------------------------------------------------- /ac1/_sources/manipulating_data/toctree.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Manipulating Data 8 | ================= 9 | 10 | .. toctree:: 11 | :caption: Contents 12 | :maxdepth: 2 13 | 14 | introduction.rst 15 | pivot_tables.rst 16 | joining_data.rst 17 | summary.rst 18 | -------------------------------------------------------------------------------- /ac1/_sources/module_b_preface.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | Module B Preface 7 | ================ 8 | 9 | In the previous module, you learned techniques to analyze data in Google Sheets. 10 | Now, it's time to learn how to analyze even larger datasets. This is especially 11 | important when you are trying to draw larger conclusions. One of the most 12 | fundamental use cases for statistics is investigating the relationship between 13 | multiple variables. When reading stories in the media, there is often discussion 14 | about links between two or more variables. For example: 15 | 16 | - `Does eating more chocolate increase your life 17 | expectancy? `__ 18 | - `Do vaccines increase the chance of autism? `__ 19 | - `Does gun ownership rate increase gun 20 | fatalities? `__ 21 | - `Does home field advantage in sports really 22 | exist? `__ 23 | - `Does reading Harry Potter reduce a person’s 24 | prejudice? `__ 25 | 26 | However, for every article with a statistical study that argues for one thing, 27 | there is usually at least one for the other side. Since there is so much news 28 | from so many diverse sources, it has become increasingly important to decipher 29 | which studies are trustworthy, what statistics are reliable, and what findings 30 | are legitimate. 31 | 32 | In the next few chapters, you will learn more about analyzing the relationship 33 | between variables. This will help you investigate the relationship between pairs 34 | of variables for your own analysis, as well as critically assess the statistical 35 | findings you read about in the media. 36 | -------------------------------------------------------------------------------- /ac1/_sources/module_c_preface.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Module C Preface 8 | ================ 9 | 10 | A lot of the data that we interact with today is stored in databases. You can 11 | think of a database as a group of tables. These tables have rows and columns 12 | just like spreadsheets. Some examples of data that can be stored in databases 13 | are listed below. 14 | 15 | - Student records, including grades, at a school 16 | - Posts and friends in your favorite social network 17 | - News stories on a newspaper’s website 18 | - Your contacts list on your mobile phone 19 | - All images that make up Google Maps 20 | 21 | All these bits of information are stored in various kinds of databases. Some of 22 | these are stored in a relational database, which is a database that stores data 23 | points that are related to one another in some way. These databases are 24 | available as open source tools like Postgresql, MySQL and SQLite, as well as 25 | commercial databases such as `Google BigQuery`_, `Oracle`_, 26 | `Microsoft SQL Server`_, or `Amazon Aurora`_. Others are stored in proprietary 27 | systems like Google’s `BigTable`_ or Facebook’s `Haystack Object Store`_. 28 | 29 | While the mechanism and content of the database may vary, there is a 30 | common language used to extract data: this language is called Structured Query 31 | Language (SQL, pronounced “sequel”). This module will teach you how you can use 32 | SQL to analyze data in a database. 33 | 34 | 35 | .. _Google BigQuery: https://cloud.google.com/bigquery/ 36 | .. _Oracle: https://www.oracle.com/database/technologies/ 37 | .. _Microsoft SQL Server: https://azure.microsoft.com/en-us/services/virtual-machines/sql-server/ 38 | .. _Amazon Aurora: https://aws.amazon.com/rds/aurora/ 39 | .. _BigTable: https://en.wikipedia.org/wiki/Bigtable 40 | .. _Haystack Object Store: https://code.fb.com/core-data/needle-in-a-haystack-efficient-storage-of-billions-of-photos/ 41 | -------------------------------------------------------------------------------- /ac1/_sources/projects/toctree.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Projects 8 | ======== 9 | 10 | .. toctree:: 11 | :caption: Projects 12 | :maxdepth: 2 13 | 14 | module_a.rst 15 | module_b.rst 16 | module_c.rst 17 | -------------------------------------------------------------------------------- /ac1/_sources/regression_and_line_of_best_fit/creating_line_of_best_fit.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | .. _creating_line_of_best_fit: 7 | 8 | Creating a Line of Best Fit 9 | =========================== 10 | 11 | In order to analyze a line of best fit for a scatter plot, you will first need 12 | to make one. You can do this in Sheets through an option in the chart editor. 13 | After making a scatter plot, you can add a line of best fit by opening the chart 14 | editor by clicking the three dots in the top right corner. 15 | 16 | 17 | .. image:: figures/edit_chart.png 18 | :align: center 19 | :alt: Screenshot showing how to edit a chart by clicking the three dots in the top right corner. 20 | 21 | Once the chart editor is open, make sure customize is selected. Under “Series”, 22 | there is a checkbox to add a trendline. You can change the color and thickness 23 | of the line, display the :math:`R^{2}` value, (this is the same as the 24 | coefficient of determination), and display the equation of the line. 25 | 26 | 27 | .. image:: figures/add_trendline.png 28 | :align: center 29 | :alt: Screenshot showing how to add trendline. 30 | 31 | Once you have added a trendline, it will appear on your graph. 32 | 33 | 34 | .. image:: figures/average_sat_score_completion_rate.png 35 | :align: center 36 | :alt: Scatter plot with a trendline. 37 | 38 | 39 | Now that there is a trendline and equation of a line on the graph, you can use 40 | this information to analyze data and predict results given your data. In 41 | particular you can use the slope and y-intercept. Don't worry if you don't 42 | remember how to find this information from the equation of a line, the next 43 | section will guide you through this. 44 | -------------------------------------------------------------------------------- /ac1/_sources/regression_and_line_of_best_fit/equation_of_a_line_refresher.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | .. _equation_of_a_line_refresher: 7 | 8 | Equation of a Line (Refresher) 9 | ============================== 10 | 11 | .. image:: figures/equation_of_a_line.png 12 | :align: center 13 | :alt: Slope intercept form: y equals m times x plus b. 14 | 15 | All line equations in this text will be presented in the form *y = mx + b*, 16 | where *m* is the slope and *b* is the y-intercept. This is also called 17 | slope-intercept form. The **y-intercept** is the y-value at the point where the 18 | line crosses the y-axis. The :ref:`slope ` gives the steepness 19 | of the line, and can be positive, negative, or zero. Slope-intercept form is a 20 | method to better understand the relationship between the two variables *x* and *y*. 21 | 22 | 23 | .. image:: figures/negative_slope.png 24 | :width: 49% 25 | :align: center 26 | :alt: A graph of the equation y equals negative one third times x plus five and the slope is negative. 27 | 28 | This figure depicts an equation of a line that has a y-intercept of 5 and a negative slope. 29 | 30 | .. image:: figures/positive_slope.png 31 | :width: 49% 32 | :align: center 33 | :alt: A graph of the equation of y equals 2 times x plus one. 34 | 35 | The equation of the line in the above figure has a y-intercept of 1 and a positive slope. 36 | 37 | For additional review on slope-intercept form you can also watch out `this video 38 | `_. 39 | -------------------------------------------------------------------------------- /ac1/_sources/regression_and_line_of_best_fit/figures/SAT_Math_and_Earnings.png: 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Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | .. _introduction_LOBF: 7 | 8 | Introduction 9 | ============ 10 | 11 | In the last section, you learned that correlation in scatter plots measures the 12 | linear relationship between two quantitative variables. The closer the 13 | coefficient of determination (or :math:`R^2` value) is to 1, and the closer the 14 | points of the scatter plot are to a straight line, the more reliable your 15 | predictions will be. But what does this line actually mean and how can it help 16 | you make predictions? 17 | 18 | This line is called the **line of best fit**, or a **regression line**. This 19 | line can be used to predict information about values that you may not have data 20 | for. A line of best fit for a scatter plot could look something like the 21 | following. 22 | 23 | .. image:: figures/average_sat_score_completion_rate.png 24 | :align: center 25 | :alt: Scatter plot with a line of best fit. 26 | 27 | In this section, you’ll learn how to create a line of best fit in Sheets, use 28 | the equation of the line of best fit to make predictions, and explain how changes 29 | in one variable may impact the other. Here are some questions a line of best fit 30 | helps to answer. 31 | 32 | - If a school has an average SAT score of 1200, what is its predicted 33 | completion rate? 34 | - If two schools have a difference of 100 points in average SAT score, will 35 | their graduates make different salaries after graduation? If so, by how much? 36 | - How does the percentage of students receiving federal loans impact completion 37 | rates? 38 | 39 | You will work through some examples throughout this section to find answers to 40 | these questions. 41 | -------------------------------------------------------------------------------- /ac1/_sources/regression_and_line_of_best_fit/summary.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | .. Location of summary document: shorturl.at/mrLNV 7 | 8 | Summary 9 | ======= 10 | 11 | .. image:: figures/regression_summary.png 12 | :align: center 13 | :alt: Graphic summarizing key concepts of regression and line of best fit. 14 | -------------------------------------------------------------------------------- /ac1/_sources/regression_and_line_of_best_fit/toctree.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Regression and "Line of Best Fit" 8 | ================================= 9 | 10 | .. toctree:: 11 | :caption: Contents 12 | :maxdepth: 2 13 | 14 | introduction.rst 15 | creating_line_of_best_fit.rst 16 | equation_of_a_line_refresher.rst 17 | interpreting_slope.rst 18 | making_predictions_with_the_regression_line.rst 19 | outliers.rst 20 | nonlinear_regression.rst 21 | summary.rst 22 | -------------------------------------------------------------------------------- /ac1/_sources/scatter_plots_and_correlation/figures/avg_if.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/scatter_plots_and_correlation/figures/avg_if.png -------------------------------------------------------------------------------- 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Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | Introduction 7 | ============ 8 | 9 | You have already learned about histograms and bar charts, which are data 10 | visualizations that are useful for understanding data. However, sometimes these 11 | visualizations are not the most intuitive for looking at individual pieces of a 12 | larger data set. This is where scatter plots come in. Scatter plots are a type 13 | of data visualization that show the relationship between two quantitative 14 | variables. An example of a scatter plot is shown below. As you can see in the 15 | screenshot, each data point is plotted individually onto a graph. By organizing 16 | data this way, it becomes easier to understand trends in larger data sets. 17 | 18 | .. image:: figures/example_scatterplot.png 19 | :align: center 20 | :alt: An example of a scatter plot 21 | 22 | In this section, you will learn how to create, read, and analyze scatter plots. 23 | You will first begin by working through an example to see why scatter plots are 24 | useful. 25 | -------------------------------------------------------------------------------- /ac1/_sources/scatter_plots_and_correlation/summary.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | .. Link to summary document: shorturl.at/mrLNV 7 | 8 | Summary 9 | ======= 10 | 11 | .. image:: figures/scatter_plots_summary.png 12 | :align: center 13 | :alt: A summary of the scatterplots section. 14 | -------------------------------------------------------------------------------- /ac1/_sources/scatter_plots_and_correlation/toctree.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Scatter Plots and Correlation 8 | ============================= 9 | 10 | .. toctree:: 11 | :caption: Contents 12 | :maxdepth: 2 13 | 14 | introduction.rst 15 | motivating_scatterplots.rst 16 | scatter_plots.rst 17 | creating_a_scatter_plot_in_sheets.rst 18 | describing_scatter_plots.rst 19 | correlation.rst 20 | correlation_and_college_data.rst 21 | correlation_versus_causation.rst 22 | correlation_and_filtering.rst 23 | summary.rst 24 | -------------------------------------------------------------------------------- /ac1/_sources/sheets_basics/figures/chocolate_cake_amounts_for_custom_servings.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/sheets_basics/figures/chocolate_cake_amounts_for_custom_servings.png -------------------------------------------------------------------------------- /ac1/_sources/sheets_basics/figures/chocolate_cake_custom_servings.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/sheets_basics/figures/chocolate_cake_custom_servings.png -------------------------------------------------------------------------------- /ac1/_sources/sheets_basics/figures/chocolate_cake_flour_for_18_servings.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/sheets_basics/figures/chocolate_cake_flour_for_18_servings.png -------------------------------------------------------------------------------- /ac1/_sources/sheets_basics/figures/chocolate_cake_flour_for_custom_servings.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/sheets_basics/figures/chocolate_cake_flour_for_custom_servings.png -------------------------------------------------------------------------------- /ac1/_sources/sheets_basics/figures/chocolate_cake_relative_referencing_not_working.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/sheets_basics/figures/chocolate_cake_relative_referencing_not_working.png -------------------------------------------------------------------------------- /ac1/_sources/sheets_basics/figures/painters_example_sheets.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/sheets_basics/figures/painters_example_sheets.png -------------------------------------------------------------------------------- /ac1/_sources/sheets_basics/figures/sheet_example.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/sheets_basics/figures/sheet_example.png -------------------------------------------------------------------------------- /ac1/_sources/sheets_basics/figures/sheets_error.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/sheets_basics/figures/sheets_error.png -------------------------------------------------------------------------------- /ac1/_sources/sheets_basics/figures/sheets_keyword_definitions.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/sheets_basics/figures/sheets_keyword_definitions.png -------------------------------------------------------------------------------- /ac1/_sources/sheets_basics/figures/sheets_summary.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/sheets_basics/figures/sheets_summary.png -------------------------------------------------------------------------------- /ac1/_sources/sheets_basics/introduction.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Introduction 8 | ============ 9 | 10 | Spreadsheets are a very powerful and widely-used tool. Spreadsheet softwares can 11 | generate graphs, do calculations extremely quickly, and even predict the future 12 | using statistics! 13 | This section introduces you to the basics of spreadsheets, and walks through a 14 | few illustrative examples. 15 | 16 | There are multiple spreadsheet softwares and the one we will focus on in this 17 | textbook is Google Sheets. While functionality may differ slightly across 18 | platforms, the core concepts and syntaxes are the same. In this course, whenever 19 | sheets are mentioned, it is in reference to Google Sheets, which is pictured 20 | below with example `student data`_. 21 | 22 | .. image:: figures/sheet_example.png 23 | :align: center 24 | :alt: Spreadsheet with example student data of name, height, hair color. 25 | 26 | .. _student data: https://docs.google.com/spreadsheets/d/1SbhCo8ZjEfFmBGwE7TLdsq-mxvMQa3hOmL5DMWF2ZTc/edit?usp=sharing -------------------------------------------------------------------------------- /ac1/_sources/sheets_basics/summary.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | .. Link to summary document: shorturl.at/mrLNV 7 | 8 | Summary 9 | ======= 10 | 11 | .. image:: figures/sheets_summary.png 12 | :align: center 13 | :alt: Graphic summarizing key concepts of Sheets basics. 14 | -------------------------------------------------------------------------------- /ac1/_sources/sheets_basics/toctree.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Sheets Basics 8 | ============= 9 | 10 | .. toctree:: 11 | :caption: Contents 12 | :maxdepth: 2 13 | 14 | introduction.rst 15 | what_is_a_sheet.rst 16 | what_is_a_formula.rst 17 | errors.rst 18 | summary.rst 19 | -------------------------------------------------------------------------------- /ac1/_sources/sql/figures/bike_dataset_columns.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/sql/figures/bike_dataset_columns.png -------------------------------------------------------------------------------- /ac1/_sources/sql/figures/sql_summary.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_sources/sql/figures/sql_summary.png -------------------------------------------------------------------------------- /ac1/_sources/sql/how_to_run_sql.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | How to Run SQL Outside of This Textbook 8 | ======================================= 9 | 10 | In this section, you learned some basic SQL commands to analyze large datasets. 11 | In the interactive version of this textbook, there was a SQL interpreter. 12 | However, when using SQL outside of the textbook, including in your project, you 13 | will need to run SQL somewhere else. In order to do this, there are many 14 | options. If you are using SQL for just this course, you can use an online 15 | interpreter, such as this one. When importing a .db file directly, select the 16 | File drop drown from the top left of the webpage and select Open DB to use your 17 | .db file. 18 | 19 | - `SQL Online Interpreter`_ 20 | 21 | Ultimately, if you plan on using SQL for more robust purposes, you will want to 22 | run SQL queries on your own machine. To do this, you will need to download a 23 | Database Engine and set up a Database Client. There are many options for 24 | database engines you can use. Some of the most popular ones are listed below. 25 | Each link takes you to the setup documentation for the database engine. Pick 26 | one that feels right to you and follow the instructions. If you would like more 27 | explanation as to which database engine you should use, read about a `comparison 28 | of relational database management systems.`_ 29 | 30 | - `SQLite`_ 31 | - `MySQL`_ 32 | - `PostgreSQL`_ 33 | - `BigQuery`_ 34 | 35 | .. _SQL Online Interpreter: https://sqliteonline.com/ 36 | .. _comparison of relational database management systems.: https://www.digitalocean.com/community/tutorials/sqlite-vs-mysql-vs-postgresql-a-comparison-of-relational-database-management-systems 37 | .. _SQLite: https://www.sqlite.org/quickstart.html 38 | .. _MySQL: https://dev.mysql.com/doc/mysql-getting-started/en/ 39 | .. _PostgreSQL: https://www.postgresql.org/docs/10/tutorial-start.html 40 | .. _BigQuery: https://cloud.google.com/bigquery/docs 41 | -------------------------------------------------------------------------------- /ac1/_sources/sql/introduction.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | Introduction 8 | ============ 9 | 10 | As mentioned in the preface, SQL (which stands for Structured Query Language) is 11 | a programming language that is used to get, store, and change information in a 12 | database. SQL is one of the most widely used programming languages today, and 13 | can be used in any field where there is data. 14 | 15 | You may be wondering when you would need to use SQL since you already know how 16 | to use Sheets. SQL does many of the things that you have learned in the previous 17 | sections, but it also does them on a much larger scale. Imagine a spreadsheet 18 | with one billion rows! 19 | 20 | You can use SQL to analyze anything from stock market prices to patient data at 21 | a major hospital. If you have a database with any kind of data, you can use SQL 22 | to store and analyze it. In addition, SQL allows you to reorganize data across 23 | different datasets. This chapter will teach you how to use SQL to automate data 24 | analysis so that you can effectively navigate large datasets that might be 25 | cumbersome to navigate by hand. 26 | -------------------------------------------------------------------------------- /ac1/_sources/sql/summary.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | .. Link to summary document: shorturl.at/mrLNV 7 | 8 | Summary 9 | ======= 10 | 11 | .. image:: figures/sql_summary.png 12 | :align: center 13 | :alt: A summary of the sql section. 14 | -------------------------------------------------------------------------------- /ac1/_sources/sql/toctree.rst: -------------------------------------------------------------------------------- 1 | .. Copyright (C) Google, Runestone Interactive LLC 2 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 3 | International License. To view a copy of this license, visit 4 | http://creativecommons.org/licenses/by-sa/4.0/. 5 | 6 | 7 | SQL 8 | === 9 | 10 | .. toctree:: 11 | :caption: Contents 12 | :maxdepth: 2 13 | 14 | introduction.rst 15 | selecting.rst 16 | filtering.rst 17 | sorting.rst 18 | aggregating.rst 19 | ifs_and_cases.rst 20 | joining.rst 21 | summary.rst 22 | how_to_run_sql.rst 23 | 24 | -------------------------------------------------------------------------------- /ac1/_static/bikeshare.db: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/ac1/_static/bikeshare.db -------------------------------------------------------------------------------- /ac1/sphinx_settings.json: -------------------------------------------------------------------------------- 1 | {"SPHINX_SOURCE_PATH": "_sources", "SPHINX_OUT_PATH": "build/ac1"} -------------------------------------------------------------------------------- /documentation/images/fixes_issue.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/documentation/images/fixes_issue.png -------------------------------------------------------------------------------- /documentation/images/new_pull_request.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/documentation/images/new_pull_request.png -------------------------------------------------------------------------------- /documentation/images/related_issue.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/documentation/images/related_issue.png -------------------------------------------------------------------------------- /documentation/images/reviewers.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/google/applied-computing-series/f7c7f4fcb73767897c35913871d2811fcdecd99c/documentation/images/reviewers.png --------------------------------------------------------------------------------