Introduction to Statistical Modelling in R

Description

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