Provides movies to help students to understand statistical 
  concepts.  The 'rpanel' package  <https://cran.r-project.org/package=rpanel> 
  is used to create interactive plots that move to illustrate key statistical 
  ideas and methods.  There are movies to: visualise probability distributions
  (including user-supplied ones); illustrate sampling distributions of the
  sample mean (central limit theorem), the median, the sample maximum 
  (extremal types theorem) and (the Fisher transformation of the) 
  product moment correlation coefficient; examine the influence of an 
  individual observation in simple linear regression; illustrate key concepts 
  in statistical hypothesis testing. Also provided are dpqr functions for the 
  distribution of the Fisher transformation of the correlation coefficient 
  under sampling from a bivariate normal distribution.

Creates images that are the proper size for social media. Beautiful
    plots, charts and graphs wither and die if they are not shared. Social media 
    is perfect for this but every platform has its own image dimensions. With 
    'smpic' you can easily save your plots with the exact dimensions needed for 
    the different platforms.

Provides functions for creating and annotating a composite plot in 'ggplot2'. Offers background themes and shortcut plotting functions that produce figures that are appropriate for the format of scientific journals. Some methods are described in Min and Zhou (2021) <doi:10.3389/fgene.2021.802894>.

Contains the datasets and a few functions for use with 
        the practicals outlined in Appendix A of the book
        Statistical Models (Davison, 2003, Cambridge University Press), 
        which can be found at <doi:10.1017/CBO9780511815850>.

Computes the studentized midrange distribution (pdf, cdf and quantile) and generates random numbers.

Produce small area population estimates by fitting census data to
    survey data.

A collection of simple parameter estimation and tests for the comparison of multivariate means and variation, to accompany Chapters 4 and 5 of the book Multivariate Statistical Methods. A Primer (5th edition), by Manly BFJ, Navarro Alberto JA & Gerow K (2024) <doi:10.1201/9781003453482>.