Contents -- Introduction -- 01 What you need to know before you start analysing data -- What is data? -- Populations and samples -- Measuring risk -- The normal distribution and sampling distributions -- 02 Analysing univariate data -- Histograms and boxplots -- Measures of location and spread -- Inference: estimation and hypothesis testing of population means -- Representing non-metric data: pie charts and bar charts -- Estimating and hypothesis testing of population proportions using sample proportions -- 03 Analysing bivariate data -- Scatter diagrams -- Correlation analysis -- Simple linear regression -- Non-linear regression -- Cluster and stacked bar charts -- Contingency analysis -- Logistic regression -- 04 Analysing multivariate data with dependency -- Preliminary analysis for multiple regression -- Multiple regression analysis -- Multiple regression model-building -- Discriminant analysis -- Multivariate analysis of variance -- An outline of canonical correlation analysis -- 05 Analysing multivariate data for interdependency -- Principal components analysis -- Factor analysis -- Cluster analysis -- Cronbach's a -- Coda -- Appendix -- Chapter 1 -- Chapter 2 -- Chapter 3 -- Chapter 4 -- Chapter 5 -- References -- Index.