Introduction to Statistical Modelling in R

University of Cambridge, Statistical Laboratory, 2012. – 114 p. – ISBN: N/AThese worksheets may be used for any educational purpose provided their authorship (P.M.E.Altham) is acknowledged.Contents:
Preface
Getting started: books and 2 tiny examples
Ways of reading in data, tables, text, matrices. Linear regression and basic plotting
A Fun example showing you some plotting and regression facilities
A one-way anova, and a qqnorm plot
A 2-way anova, how to set up factor levels, and boxplots
A 2-way layout with missing data, ie an unbalanced design
Logistic regression for the binomial distribution
The space shuttle temperature data: a cautionary tale
Binomial and Poisson regression
Analysis of a 2-way contingency table
Poisson regression: some examples
Fisher’s exact test, 3-way contingency tables, and Simpson’s paradox
Defining a function in R, to plot the contours of a log-likelihood function
Regression diagnostics continued, and the hat matrix
Football arrests, Poisson and the negative binomial regressions
An interesting data set on Election turnout and poll leads
glm() with the gamma distribution
Crime and unemployment: a case-control study
Maximising a multi-parameter log-likelihood: an example from genomics
Miscellaneous datasets gathered in 2006
An application of the Bradley-Terry model to the Corus chess tournament, and to World Cup football
Brief introduction to Survival Data Analysis
The London 2012 Olympics Men’s 200 metres, and reading data off the webIndex