├── README.md └── TeachingStatistics.md /README.md: -------------------------------------------------------------------------------- 1 | ## CRAN Task View: Teaching Statistics 2 | 3 | **URL:** 4 | 5 | **Source file:** [TeachingStatistics.md](TeachingStatistics.md) 6 | 7 | **Contributions:** Suggestions and improvements for this task view are very 8 | welcome and can be made through issues or pull requests here on GitHub or 9 | via e-mail to the maintainer address. For further details see the 10 | [Contributing](https://github.com/cran-task-views/ctv/blob/main/Contributing.md) 11 | guide. All contributions must adhere to the 12 | [code of conduct](https://github.com/cran-task-views/ctv/blob/main/CodeOfConduct.md). 13 | -------------------------------------------------------------------------------- /TeachingStatistics.md: -------------------------------------------------------------------------------- 1 | --- 2 | name: TeachingStatistics 3 | topic: Teaching Statistics 4 | maintainer: Paul Northrop 5 | email: p.northrop@ucl.ac.uk 6 | version: 2022-12-16 7 | source: https://github.com/cran-task-views/TeachingStatistics/ 8 | --- 9 | 10 | 11 | This CRAN task view gives information about packages with features that 12 | are designed to assist with the teaching of Statistics. It is **not** 13 | concerned with the teaching of R itself. A few of these packages are 14 | listed in other task views, but only the 15 | `r view("Bayesian")` task view has a section devoted 16 | explicitly to teaching (Bayesian) Statistics. 17 | 18 | The packages are grouped into three broad topics: teaching, examination 19 | and packages associated with Statistics books. The latter is for books 20 | that are general enough to be of potential interest to a wide audience 21 | of teachers of Statistics. They should concern models and methods with 22 | wide applicability and not be tied closely to a particular application. 23 | 24 | If you think that a package is missing from the list, or have any other 25 | comments or suggestions, then please contact the maintainer, either via 26 | e-mail or by submitting an issue or pull request in the GitHub repository 27 | linked above. 28 | 29 | ### Teaching 30 | 31 | - `r pkg("Rcmdr", priority = "core")` provides a GUI for R, 32 | based on the tcltk package. A point-and-click interface loads data 33 | and calls R functions to perform the kinds of analyses involved in 34 | introductory Statistics courses. More advanced and specialized 35 | analysis are also available, some of them via plug-ins. The R 36 | commands are shown in the console. See the [The R Commander 37 | homepage](https://socialsciences.mcmaster.ca/jfox/Misc/Rcmdr/) for 38 | more information. 39 | - `r pkg("swirl")` uses the R console to provide an 40 | interactive learning environment for students to learn Statistics. 41 | Students select courses to download from the 42 | `r github("swirldev/swirl_courses")` GitHub page and 43 | are provided with immediate feedback as they work. A variety of 44 | topics are available, under the general headings of Exploratory Data 45 | Analysis, Statistical Inference and Regression Models. Teachers can 46 | author and share their own swirl courses using the 47 | `r pkg("swirlify")` package. See also the [swirl home 48 | page.](https://swirlstats.com/) 49 | - `r pkg("mosaic", priority = "core")` contains a wide 50 | range of tools to assist in teaching of basic, and more advanced 51 | ideas and techniques in mathematics, statistics, computation and 52 | modelling. Key aspects are the provision of functions that enable 53 | beginners easily to perform tasks that would otherwise be difficult 54 | and the use of simulation to illustrate randomization-based 55 | inference. See the [Project MOSAIC homepage](http://www.mosaic-web.org) 56 | for more information. 57 | - `r pkg("xplain")` can be used to provide bespoke 58 | interactive interpretations of the output from statistics functions. 59 | This information needs to be provided by the instructor in XML 60 | format and may contain R code, to tailor the explanation to the 61 | specific results. See the [xplain 62 | website](https://www.zuckarelli.de/xplain/index.html) for a tutorial 63 | and cheatsheet. 64 | - `r pkg("animation", priority = "core")` provides 65 | functions to produce animations relating to a wide range of topics 66 | in Statistics, Data Mining and Machine Learning. These animations, 67 | or a sequence of images generated by the user, may be exported to a 68 | variety of formats. 69 | - `r pkg("gganimate")` animates plots produced by 70 | `r pkg("ggplot2")`. It can be used to render the plots 71 | into an animation, such as a GIF or MP4 video . 72 | - `r pkg("smovie")` provides movies to illustrate concepts 73 | in Statistics. Topics covered are: probability distributions; 74 | sampling distributions of the mean (cf. central limit theorem), the 75 | maximum (cf. extremal types theorem) and the (Fisher transformation 76 | of the) correlation coefficient; simple linear regression; 77 | hypothesis testing. 78 | - `r pkg("visualize")` provides graphs of the pdf/pmf of 79 | various continuous and discrete probability distributions, annotated 80 | with the mean and variance of the distribution. Shading is used to 81 | indicate an interval (lower tail, upper tail, two-tailed or a 82 | user-supplied interval) within which the random variable lies with a 83 | user-supplied probability. 84 | - `r pkg("LearnBayes")` provides functions and to 85 | illustrate the essential ideas of Bayesian inference, such as the 86 | roles of the prior, likelihood and posterior; posterior predictive 87 | checking and predictive inference, and several example datasets. 88 | - `r pkg("shinybrms")` provides a shiny app for fitting Bayesian 89 | generalized (non-)linear multivariate multilevel regression models 90 | [brms](https://paul-buerkner.github.io/brms/) package. Help text 91 | leads the user through the steps of uploading a dataset, specifying 92 | a likelihood, setting a prior distribution and making inferences about 93 | the posterior distribution. See the package 94 | [README](https://cran.r-project.org/web/packages/shinybrms/readme/README.html) 95 | file and the [Getting started](https://fweber144.github.io/shinybrms/articles/shinybrms.html) page. 96 | - `r pkg("TeachingDemos")` Provides a wide range of static 97 | and interactive plots to demonstrate statistical concepts, 98 | including: coin tossing and dice rolling; confidence intervals; 99 | various aspects of hypothesis testing; the central limit theorem; 100 | maximum likelihood estimation; scatterplot smoothing; histograms; 101 | correlation and simple linear regression; Box-Cox transformation. 102 | - `r pkg("distrTeach")` provides plots to illustate the 103 | Central Limit Theorem (CLT) and the Law of Large Numbers (LLN). The 104 | effects on the CLT plots of changing inputs can be shown using a 105 | Tcl/Tk-based widget. 106 | - `r pkg("BetaBit")` provides games for students to play 107 | in the R console, including one that involves data-cleaning and 108 | regression modelling. See the [BetaBit home 109 | page](http://betabit.wiki/) . 110 | - `r pkg("DALEX")` provides functions to explore and 111 | understand predictive models. The [DALEX GitHub 112 | page](https://github.com/ModelOriented/DALEX) includes two 113 | teaching-related showcases. 114 | 115 | ### Examination 116 | 117 | - `r pkg("exams", priority = "core")` provides a framework 118 | for the automatic random generation of exams and self-study 119 | materials from a pool of exercises composed using either Sweave 120 | (.Rnw) or R markdown (.Rmd) formats. R code can be used to generate 121 | exercise elements dynamically. Questions can be formatted for use in 122 | a variety of e-learning platforms or output as documents, for 123 | example a PDF file, for which. Scans of PDF answer sheets can be 124 | marked automatically. See also the [R/exams 125 | homepage](http://www.R-exams.org) 126 | - `r pkg("ProfessR")` creates multiple choice exams from a 127 | pool of exercises organised in ASCII test files. Multiple versions 128 | of an exam can be created by randomizing the questions and the 129 | choices of answers. 130 | - `r pkg("TexExamRandomizer")` enables the randomization 131 | of questions created using LaTeX's document class for preparing 132 | exams. Spreadsheets containing students' answers can be marked 133 | automatically. 134 | 135 | ### Packages associated with Statistics books 136 | 137 | The following packages are associated with textbooks that are of 138 | potential interest to a general statistical audience, rather than being 139 | specific to a particular application area. The general principle for 140 | inclusion is that package is likely to be of direct use in the teaching 141 | of statistical methods. Official publisher links are provided where 142 | possible and, in some cases, a link to further resources. 143 | 144 | - `r pkg("AER")`: Kleiber, C. and Zeileis, A. (2008), 145 | [Applied Econometrics with 146 | R](https://doi.org/10.1007/978-0-387-77318-6) , Springer Verlag, New 147 | York. [Further 148 | resources](https://eeecon.uibk.ac.at/~zeileis/teaching/AER/) . 149 | - `r pkg("arm")`: Gelman, A. and Hill, J. (2007), [Data 150 | Analysis Using Regression and Multilevel/Hierarchical 151 | Models](https://doi.org/10.1017/CBO9780511790942) , Cambridge 152 | University Press. [Further 153 | resources](http://www.stat.columbia.edu/~gelman/arm/) . 154 | - `r pkg("ACSWR")`: Tattar, P.N., Suresh, R., and 155 | Manjunath, B.G. (2016), [A Course in Statistics With 156 | R](https://doi.org/10.1002/9781119152743) , John Wiley and Sons, 157 | Inc. 158 | - `r pkg("BayesDA", priority = "core")`: Gelman, A., 159 | Carlin, J., Stern, H., Dunson, D., Vehtari, A., Rubin, D. (2013), 160 | [Bayesian Data 161 | Analysis](https://www.crcpress.com/Bayesian-Data-Analysis-Third-Edition/Gelman-Carlin-Stern-Dunson-Vehtari-Rubin/p/book/9781439840955) 162 | , Third Edition. New York: Chapman and Hall/CRC. [Further 163 | resources](http://www.stat.columbia.edu/~gelman/book/) . 164 | - `r pkg("Bolstad")`: Bolstad, W. M. and Curran, J. M. 165 | (2016), [Introduction to Bayesian 166 | Statistics](https://doi.org/10.1002/9781118593165) , Third Edition. 167 | John Wiley and Sons, Inc. 168 | - `r pkg("car")`, `r pkg("carData")`, 169 | `r pkg("effects")`: Fox, J, and Weisberg, S. (2019), [An 170 | R Companion to Applied 171 | Regression](https://uk.sagepub.com/en-gb/eur/an-r-companion-to-applied-regression/book246125) 172 | , Springer Verlag, New York. [Further 173 | resources](https://socialsciences.mcmaster.ca/jfox/Books/Companion/index.html) 174 | . 175 | - `r pkg("faraway")`: Three books by Julian Faraway: 176 | [Practical Regression and ANOVA in 177 | R](https://cran.r-project.org/doc/contrib/Faraway-PRA.pdf) (CRAN 178 | document), [Linear Models with 179 | R](https://www.crcpress.com/Linear-Models-with-R-Second-Edition/Faraway/p/book/9781439887332) 180 | (2014), CRC Press, [Extending the Linear Model with 181 | R](https://www.crcpress.com/Extending-the-Linear-Model-with-R-Generalized-Linear-Mixed-Effects-and/Faraway/p/book/9781498720960) 182 | (2016), CRC Press. 183 | - `r pkg("HH")`: Heiberger, R. M. and Holland B. (2015), 184 | [Statistical Analysis and Data Display: An Intermediate Course with 185 | Examples in R](https://doi.org/10.1007/978-1-4939-2122-5) , Second 186 | edition. Springer-Verlag, New York. 187 | - `r pkg("HKRbook")`: Härdle, W. K., Klinke, S. and Rönz, B. (2015), 188 | [Introduction to Statistics](https://doi.org/10.1007%2F978-3-319-17704-5). 189 | Springer Verlag, New York. [Further resources](https://extras.springer.com/?query=978-3-319-17703-8). 190 | - `r pkg("HSAUR3")`: Hothorn, T. and Everitt, B. S. 191 | (2014), [A Handbook of Statistical Analyses using 192 | R](https://www.crcpress.com/A-Handbook-of-Statistical-Analyses-using-R-Third-Edition/Hothorn-Everitt/p/book/9781482204582) 193 | , Third Edition. New York: Chapman and Hall/CRC. 194 | - `r pkg("ISwR")`: Dalgaard, P. (2008), [Introductory 195 | Statistics with R](https://doi.org/10.1007/978-0-387-79054-1) , 196 | Second Edition, Springer Verlag, New York. 197 | - `r pkg("MASS", priority = "core")`: Venables, W. N. and 198 | Ripley, B. D. (2002) [Modern Applied Statistics with 199 | S](https://www.springer.com/gb/book/9780387954578) , Fourth Edition, 200 | Springer, New York. [Further 201 | resources](http://www.stats.ox.ac.uk/pub/MASS4) . 202 | - `r pkg("moderndive")`: Ismay, C. and Kim, A. Y. (2019) 203 | [ModernDive: Statistical Inference via Data 204 | Science](https://moderndive.com/) . See also 205 | `r pkg("infer")`. 206 | - `r pkg("MPV")`: Montgomery, D.C., Peck, E. A. and 207 | Vining, G. (2012), [Introduction to Linear Regression 208 | Analysis](https://www.wiley.com/en-gb/Introduction+to+Linear+Regression+Analysis%2C+6th+Edition-p-00029190) 209 | , John Wiley and Sons, Inc. 210 | - `r pkg("msos")`: Marden, J. (2015) [Multivariate 211 | Statistics: Old School](%20http://istics.net/stat/Multivariate/) , 212 | CreateSpace Independent Publishing Platform. [Free PDF 213 | version](http://istics.net/pdfs/multivariate.pdf) . 214 | - `r pkg("openintro")`: Open-source textbooks and resources for introductory statistics published 215 | by [OpenIntro](https://www.openintro.org/). 216 | - `r pkg("regtools")`: Matloff, N. (2017), [Statistical 217 | Regression and Classification: from Linear Models to Machine 218 | Learning](https://www.crcpress.com/Statistical-Regression-and-Classification-From-Linear-Models-to-Machine/Matloff/p/book/9781498710916) 219 | , New York: Chapman and Hall/CRC. 220 | - `r pkg("resampledata")`: Chihara, L. M. and 221 | Hesterberg, T. C. (2018), [Mathematical Statistics with Resampling 222 | in 223 | R](https://www.wiley.com/en-us/Mathematical+Statistics+with+Resampling+and+R%2C+2nd+Edition-p-9781119416531) 224 | , Second Edition, John Wiley and Sons, Inc. [Further 225 | resources](https://sites.google.com/site/chiharahesterberg/) . 226 | - `r pkg("Sleuth2")` and `r pkg("Sleuth3")`: 227 | Ramsey, F. and Schafer, D. (2013), [The Statistical Sleuth: a Course 228 | in Methods of Data Analysis](http://www.statisticalsleuth.com/) , 229 | Brooks / Cole Cengage Learning. 230 | - `r pkg("SMPracticals")`: Davison, A. C. (2003), 231 | [Statistical Models](https://doi.org/10.1017/CBO9780511815850) , 232 | Cambridge University Press. [Further 233 | resources](http://statwww.epfl.ch/davison/SM/) . 234 | - `r pkg("vcd")`: Friendly, M. and Meyer, D. (2015), 235 | [Discrete Data Analysis with 236 | R](https://www.crcpress.com/Discrete-Data-Analysis-with-R-Visualization-and-Modeling-Techniques-for/Friendly-Meyer/p/book/9781498725835) 237 | , New York: Chapman and Hall/CRC. [Further 238 | resources](http://ddar.datavis.ca/) . 239 | - `r pkg("wooldridge")`: Wooldridge, J. M. (2016), 240 | [Introductory Econometrics: A Modern 241 | Approach](https://www.cengage.uk/shop/isbn/9781337558860) , Seventh 242 | edition, CENGAGE Learning Custom Publishing. 243 | 244 | 245 | 246 | ### Links 247 | - [Mailing list: R Special Interest Group on Teaching Statistics using R](https://stat.ethz.ch/mailman/listinfo/r-sig-teaching) 248 | - [ABC News' FiveThirtyEight: opinion poll, politics, economics and sports datasets, blogs and some R code.](https://data.fivethirtyeight.com/) 249 | - [The fivethirtyeight package: unofficial collection of datasets and code from FiveThirtyEight.](https://CRAN.R-project.org/package=fivethirtyeight) 250 | - [R/exams homepage](http://www.R-exams.org/) 251 | - [OpenIntro text books and R Labs](https://www.openintro.org/) 252 | - [Project MOSAIC homepage](http://mosaic-web.org/) 253 | - [The R Commander homepage](https://socialsciences.mcmaster.ca/jfox/Misc/Rcmdr/) 254 | - [The swirl home page](https://swirlstats.com/) 255 | --------------------------------------------------------------------------------