---
name: TeachingStatistics
topic: Teaching Statistics
maintainer: Paul Northrop
email: p.northrop@ucl.ac.uk
version: 2024-08-01
source: https://github.com/cran-task-views/TeachingStatistics/
---


This CRAN task view gives information about packages with features that
are designed to assist with the teaching of Statistics. It is **not**
concerned with the teaching of R itself. A few of these packages are
listed in other task views, but only the
`r view("Bayesian")` task view has a section devoted
explicitly to teaching (Bayesian) Statistics.

The packages are grouped into three broad topics: teaching, examination
and packages associated with Statistics books. The latter is for books
that are general enough to be of potential interest to a wide audience
of teachers of Statistics. They should concern models and methods with
wide applicability and not be tied closely to a particular application.

If you think that a package is missing from the list, or have any other
comments or suggestions, then please contact the maintainer, either via
e-mail or by submitting an issue or pull request in the GitHub repository
linked above.

### Teaching

-   `r pkg("Rcmdr", priority = "core")` provides a GUI for R,
    based on the tcltk package. A point-and-click interface loads data
    and calls R functions to perform the kinds of analyses involved in
    introductory Statistics courses. More advanced and specialized
    analysis are also available, some of them via plug-ins. The R
    commands are shown in the console. See the [The R Commander
    homepage](https://socialsciences.mcmaster.ca/jfox/Misc/Rcmdr/) for
    more information.
-   `r pkg("swirl")` uses the R console to provide an
    interactive learning environment for students to learn Statistics.
    Students select courses to download from the
    `r github("swirldev/swirl_courses")` GitHub page and
    are provided with immediate feedback as they work. A variety of
    topics are available, under the general headings of Exploratory Data
    Analysis, Statistical Inference and Regression Models. Teachers can
    author and share their own swirl courses using the
    `r pkg("swirlify")` package. See also the [swirl home
    page.](https://swirlstats.com/)
-   `r pkg("mosaic", priority = "core")` contains a wide
    range of tools to assist in teaching of basic, and more advanced
    ideas and techniques in mathematics, statistics, computation and
    modelling. Key aspects are the provision of functions that enable
    beginners easily to perform tasks that would otherwise be difficult
    and the use of simulation to illustrate randomization-based
    inference. See the [Project MOSAIC homepage](http://www.mosaic-web.org)
    for more information.
-   `r pkg("xplain")` can be used to provide bespoke
    interactive interpretations of the output from statistics functions.
    This information needs to be provided by the instructor in XML
    format and may contain R code, to tailor the explanation to the
    specific results. See the [xplain
    website](https://www.zuckarelli.de/xplain/index.html) for a tutorial
    and cheatsheet.
-   `r pkg("animation", priority = "core")` provides
    functions to produce animations relating to a wide range of topics
    in Statistics, Data Mining and Machine Learning. These animations,
    or a sequence of images generated by the user, may be exported to a
    variety of formats.
-   `r pkg("gganimate")` animates plots produced by
    `r pkg("ggplot2")`. It can be used to render the plots
    into an animation, such as a GIF or MP4 video .
-   `r pkg("smovie")` provides movies to illustrate concepts
    in Statistics. Topics covered are: probability distributions;
    sampling distributions of the mean (cf. central limit theorem), the
    maximum (cf. extremal types theorem) and the (Fisher transformation
    of the) correlation coefficient; simple linear regression;
    hypothesis testing.
-   `r pkg("visualize")` provides graphs of the pdf/pmf of
    various continuous and discrete probability distributions, annotated
    with the mean and variance of the distribution. Shading is used to
    indicate an interval (lower tail, upper tail, two-tailed or a
    user-supplied interval) within which the random variable lies with a
    user-supplied probability.
-   `r pkg("LearnBayes")` provides functions and to
    illustrate the essential ideas of Bayesian inference, such as the
    roles of the prior, likelihood and posterior; posterior predictive
    checking and predictive inference, and several example datasets.
-   `r pkg("shinybrms")` provides a shiny app for fitting various types of 
     Bayesian regression models using the 
     [brms](https://paul-buerkner.github.io/brms/) package. Help text leads 
     the user through the steps of uploading a dataset, specifying 
     a likelihood, setting a prior distribution and making inferences about 
     the posterior distribution. See the package 
     [README](https://cran.r-project.org/web/packages/shinybrms/readme/README.html) 
     file and the 
     [Getting started](https://fweber144.github.io/shinybrms/articles/shinybrms.html) 
     page. 
-   `r pkg("TeachingDemos")` Provides a wide range of static
    and interactive plots to demonstrate statistical concepts,
    including: coin tossing and dice rolling; confidence intervals;
    various aspects of hypothesis testing; the central limit theorem;
    maximum likelihood estimation; scatterplot smoothing; histograms;
    correlation and simple linear regression; Box-Cox transformation.
-   `r pkg("distrTeach")` provides plots to illustrate the
    Central Limit Theorem (CLT) and the Law of Large Numbers (LLN). The
    effects on the CLT plots of changing inputs can be shown using a
    Tcl/Tk-based widget.
-   `r pkg("BetaBit")` provides games for students to play
    in the R console, including one that involves data-cleaning and
    regression modelling. See the [BetaBit home
    page](http://betabit.wiki/) .
-   `r pkg("DALEX")` provides functions to explore and
    understand predictive models. The [DALEX GitHub
    page](https://github.com/ModelOriented/DALEX) includes two
    teaching-related showcases.
-   `r pkg("agricolae")` provides functionality assist the teaching of the 
    design and analysis of statistical experiments, with an emphasis on 
    agricultural field experiments. Designs constructed by `r pkg("agricolae")` 
    can be visualised using `r pkg("agricolaeplotr")`.
-   `r pkg("LearningRlab")` is designed to help teach basic statistics to 
    secondary and baccalaureate students. It has functions that provide 
    step-by-step explanations of statistical calculations and functions that
    prompt the student to perform their own calculations. See the package 
    vignette for examples.
    
### Examination

-   `r pkg("exams", priority = "core")` provides a framework
    for the automatic random generation of exams and self-study
    materials from a pool of exercises composed using either Sweave
    (.Rnw) or R markdown (.Rmd) formats. R code can be used to generate
    exercise elements dynamically. Questions can be formatted for use in
    a variety of e-learning platforms or output as documents, for
    example a PDF file, for which. Scans of PDF answer sheets can be
    marked automatically. See also the [R/exams
    homepage](http://www.R-exams.org)
-   `r pkg("ProfessR")` creates multiple choice exams from a
    pool of exercises organised in ASCII test files. Multiple versions
    of an exam can be created by randomizing the questions and the
    choices of answers.
-   `r pkg("rqti")` creates exercises and exams in adherence to the 
    QTI v2.1 standard directly from R. Users have the flexibility to 
    render the exercises either locally (using `qti.js`) or integrate them 
    seamlessly into the OPAL learning management system. Exercises can be 
    created as R Markdown files or as `rqti` S4 classes. See also the 
    [rqti homepage](https://shevandrin.github.io/rqti/).
-   `r pkg("TexExamRandomizer")` enables the randomization
    of questions created using LaTeX's document class for preparing
    exams. Spreadsheets containing students' answers can be marked
    automatically.

### Packages associated with Statistics books

The following packages are associated with textbooks that are of
potential interest to a general statistical audience, rather than being
specific to a particular application area. The general principle for
inclusion is that the package is likely to be of direct use in the teaching
of statistical methods. Official publisher links are provided where
possible and, in some cases, a link to further resources.

-   `r pkg("ACSWR")`: Tattar, P.N., Suresh, R., and
    Manjunath, B.G. (2016), [A Course in Statistics With
    R](https://doi.org/10.1002/9781119152743) , John Wiley and Sons,
    Inc.
-   `r pkg("AER")`: Kleiber, C. and Zeileis, A. (2008),
    [Applied Econometrics with
    R](https://doi.org/10.1007/978-0-387-77318-6) , Springer Verlag, New
    York. [Further
    resources](https://eeecon.uibk.ac.at/~zeileis/teaching/AER/).
-   `r pkg("arm")`: Gelman, A. and Hill, J. (2007), [Data
    Analysis Using Regression and Multilevel/Hierarchical
    Models](https://doi.org/10.1017/CBO9780511790942) , Cambridge
    University Press. [Further
    resources](http://www.stat.columbia.edu/~gelman/arm/).
-   `r pkg("asbio")`: Aho, K. A. (2014), [Foundational and applied statistics for biologists using R](https://www.routledge.com/Foundational-and-Applied-Statistics-for-Biologists-Using-R/Aho/p/book/9781032477411), Routledge. [Further
    resources](https://www2.cose.isu.edu/~ahoken/book/).
-   `r pkg("BayesDA", priority = "core")`: Gelman, A.,
    Carlin, J., Stern, H., Dunson, D., Vehtari, A., Rubin, D. (2013),
    [Bayesian Data
    Analysis](https://www.crcpress.com/Bayesian-Data-Analysis-Third-Edition/Gelman-Carlin-Stern-Dunson-Vehtari-Rubin/p/book/9781439840955)
    , Third Edition. New York: Chapman and Hall/CRC. [Further
    resources](http://www.stat.columbia.edu/~gelman/book/).
-   `r pkg("Bolstad")`: Bolstad, W. M. and Curran, J. M.
    (2016), [Introduction to Bayesian
    Statistics](https://doi.org/10.1002/9781118593165) , Third Edition.
    John Wiley and Sons, Inc.
-   `r pkg("car")`, `r pkg("carData")`,
    `r pkg("effects")`: Fox, J, and Weisberg, S. (2019), [An
    R Companion to Applied
    Regression](https://uk.sagepub.com/en-gb/eur/an-r-companion-to-applied-regression/book246125)
    , Springer Verlag, New York. [Further
    resources](https://socialsciences.mcmaster.ca/jfox/Books/Companion/index.html)
    .
-   `r pkg("CatDataAnalysis")`: Agresti, A. (2013), [Categorical Data Analysis](https://www.wiley.com/en-gb/Categorical+Data+Analysis%2C+3rd+Edition-p-9780470463635), Third Edition, John Wiley and Sons, Inc.
-   `r pkg("faraway")`: Three books by Julian Faraway:
    [Practical Regression and ANOVA in
    R](https://cran.r-project.org/doc/contrib/Faraway-PRA.pdf) (CRAN
    document), [Linear Models with
    R](https://www.crcpress.com/Linear-Models-with-R-Second-Edition/Faraway/p/book/9781439887332)
    (2014), CRC Press, [Extending the Linear Model with
    R](https://www.crcpress.com/Extending-the-Linear-Model-with-R-Generalized-Linear-Mixed-Effects-and/Faraway/p/book/9781498720960)
    (2016), CRC Press.
-   `r pkg("HH")`: Heiberger, R. M. and Holland B. (2015),
    [Statistical Analysis and Data Display: An Intermediate Course with
    Examples in R](https://doi.org/10.1007/978-1-4939-2122-5) , Second
    edition. Springer-Verlag, New York.
-   `r pkg("HKRbook")`: Härdle, W. K., Klinke, S. and Rönz, B. (2015), 
    [Introduction to Statistics](https://doi.org/10.1007%2F978-3-319-17704-5). 
    Springer Verlag, New York. [Further resources](https://extras.springer.com/?query=978-3-319-17703-8).    
-   `r pkg("HRW")`: Harezlak J., Ruppert D., and Wand M. P. (2018), 
    [Semiparametric Regression with R](https://doi.org/10.1007/978-1-4939-8853-2). 
    Springer Verlag, New York. [Further resources](http://www.semiparametric-regression-with-r.net/).
-   `r pkg("HSAUR3")`: Hothorn, T. and Everitt, B. S.
    (2014), [A Handbook of Statistical Analyses using
    R](https://www.crcpress.com/A-Handbook-of-Statistical-Analyses-using-R-Third-Edition/Hothorn-Everitt/p/book/9781482204582)
    , Third Edition. New York: Chapman and Hall/CRC.
-   `r pkg("ISwR")`: Dalgaard, P. (2008), [Introductory
    Statistics with R](https://doi.org/10.1007/978-0-387-79054-1) ,
    Second Edition, Springer Verlag, New York.
-   `r pkg("MASS", priority = "core")`: Venables, W. N. and
    Ripley, B. D. (2002) [Modern Applied Statistics with
    S](https://www.springer.com/gb/book/9780387954578) , Fourth Edition,
    Springer, New York. [Further
    resources](http://www.stats.ox.ac.uk/pub/MASS4).
-   `r pkg("moderndive")`: Ismay, C. and Kim, A. Y. (2019)
    [ModernDive: Statistical Inference via Data
    Science](https://moderndive.com/) . See also
    `r pkg("infer")`.
-   `r pkg("MPV")`: Montgomery, D.C., Peck, E. A. and
    Vining, G. (2012), [Introduction to Linear Regression
    Analysis](https://www.wiley.com/en-gb/Introduction+to+Linear+Regression+Analysis%2C+6th+Edition-p-00029190)
    , John Wiley and Sons, Inc.
-   `r pkg("msos")`: Marden, J. (2015) [Multivariate
    Statistics: Old School](%20http://istics.net/stat/Multivariate/) ,
    CreateSpace Independent Publishing Platform. [Free PDF
    version](http://istics.net/pdfs/multivariate.pdf).
-   `r pkg("openintro")`: Open-source textbooks and resources for introductory statistics published
    by [OpenIntro](https://www.openintro.org/).
-   `r pkg("regtools")`: Matloff, N. (2017), [Statistical
    Regression and Classification: from Linear Models to Machine
    Learning](https://www.crcpress.com/Statistical-Regression-and-Classification-From-Linear-Models-to-Machine/Matloff/p/book/9781498710916)
    , New York: Chapman and Hall/CRC.
-   `r pkg("resampledata")`: Chihara, L. M. and
    Hesterberg, T. C. (2018), [Mathematical Statistics with Resampling
    in
    R](https://www.wiley.com/en-us/Mathematical+Statistics+with+Resampling+and+R%2C+2nd+Edition-p-9781119416531)
    , Second Edition, John Wiley and Sons, Inc. [Further
    resources](https://sites.google.com/site/chiharahesterberg/).
-   `r pkg("Sleuth2")` and `r pkg("Sleuth3")`:
    Ramsey, F. and Schafer, D. (2013), [The Statistical Sleuth: a Course
    in Methods of Data Analysis](http://www.statisticalsleuth.com/) ,
    Brooks / Cole Cengage Learning.
-   `r pkg("SMPracticals")`: Davison, A. C. (2003),
    [Statistical Models](https://doi.org/10.1017/CBO9780511815850) ,
    Cambridge University Press. [Further
    resources](http://statwww.epfl.ch/davison/SM/).
-   `r pkg("vcd")`, `r pkg("vcdExtra")`: Friendly, M. and Meyer, D. (2015),
    [Discrete Data Analysis with
    R](https://www.crcpress.com/Discrete-Data-Analysis-with-R-Visualization-and-Modeling-Techniques-for/Friendly-Meyer/p/book/9781498725835)
    , New York: Chapman and Hall/CRC. [Further
    resources](http://ddar.datavis.ca/).
-   `r pkg("wooldridge")`: Wooldridge, J. M. (2016),
    [Introductory Econometrics: A Modern
    Approach](https://www.cengage.uk/shop/isbn/9781337558860) , Seventh
    edition, CENGAGE Learning Custom Publishing.



### Links
-   [Mailing list: R Special Interest Group on Teaching Statistics using R](https://stat.ethz.ch/mailman/listinfo/r-sig-teaching)
-   [ABC News' FiveThirtyEight: opinion poll, politics, economics and sports datasets, blogs and some R code.](https://data.fivethirtyeight.com/)
-   [The fivethirtyeight package: unofficial collection of datasets and code from FiveThirtyEight.](https://CRAN.R-project.org/package=fivethirtyeight)
-   [R/exams homepage](http://www.R-exams.org/)
-   [OpenIntro text books and R Labs](https://www.openintro.org/)
-   [Project MOSAIC homepage](http://mosaic-web.org/)
-   [The R Commander homepage](https://socialsciences.mcmaster.ca/jfox/Misc/Rcmdr/)
-   [The swirl home page](https://swirlstats.com/)