Introductory e-books 
Three e-books teaching introductory statistics using data sets and scenarios from different application areas.
Exercises 
A collection of exercises to accompany the introductory e-books.
- Exercises
- This e-book contains a collection of exercises that will eventually cover all introductory material but
currently only goes as far as confidence intervals. The exercises are interactive with feedback about mistakes and a button
to give the correct answer. Each exercise contains enough random aspects that it can be repeated until the concept is
mastered.
(Click to display e-book in a new window)
Advanced e-books 
Four e-books that teach advanced topics (multiple regression, experimental design for agriculture and biology, industrial experiments and theoretical statistics).
- Multiple regression and GLMs
- This e-book starts with simple linear regression, then extends it to models with more
explanatory variables including multicollinearity, interaction and diagnostics. It then covers analysis of variance,
matrix representation of models, and the use of indicator variables and factors. A final chapter gives some distribution
theory.
- Experiments in agriculture and biology
- This e-book describes principles for experimental design with emphasis on situations where the experimental units are very variable. It also shows how the resulting data can be analysed. The e-book starts with chapters about experiments with one and two factors, then examines how blocking of experimental units improves the accuracy of estimates. Later chapters describe incomplete blocks, split plot designs and covariates.
- Industrial experiments
- This e-book contains topics relevant to the design and analysis of industrial experiments. After an introductory chapter about experiments with one and two factors and interaction, it covers factorial experiments, fractional factorial experiments, response surfaces and models for mixtures.
- Statistical theory
- This e-book describes some of the mathematical theory that underpins statistical methods. It covers probability, discrete and continuous distributions, inference (including likelihood methods), transformed variables and an introduction to bivariate distributions.
(Click to display e-book in a new window)
Extra e-booklets 
Two short e-books teach additional topics (simulation and data presentation). A case study about nonlinear regression and an e-book about interpreting class marks are also provided.
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- Simulation and sport
- Simulations provide a useful tool to analyse complex models. This module describes probability models for various sports and uses simulations to gain insight into results.
- Data presentation
- This module describes effictive data presentation in tables, graphs and maps. The principles are general but most examples used are from official statistics.
- Interpreting class marks
- This module was developed to help teachers understand and process the marks of students. It starts with simple graphical and numerical ways to summarise marks then describes the use of z-scores, stanines and scaling.
- Nonlinear regression case study
- This module is a case study using a data set about the weight and length of slugs.
(Click to display module in a new window)
Applets for lecturers 
These e-books contain the interactive diagrams from the three basic e-books in a format better suited to lectures.
To maximise the window space available to CAST, the selected e-book will start
in a new window without toolbars at the top unless the following checkbox is clicked.