List of Figures. List of Tables. List of Boxes. Preface. Acknowledgements. Introduction. Averages, Measures of Dispersal and the t-test. Using Variance to Test Hypotheses. Calculating F Ratios for One-factor Between-subjects Designs. One-factor Between-subjects ANOVA: Advanced Topics. Following up a One-factor Between-subjects ANOVA. Calculating F Ratios for One-factor Within-subjects Designs. An Introduction to Factorial Designs and Interactions. Calculating F Ratios for Two-factor Between-subjects Designs. Following up a Two-factor Between-subjects ANOVA. Interpreting Two-factor Mixed and Within-subjects Designs. Interpreting a Three-factor ANOVA. Summary and Frequently Asked Questions. Appendix A: Writing up the Results of Analysis of Variance. Appendix B: Statistical Tables. Notes. References. Index.
In the investigation of human behaviour, statistical techniques are employed widely in the social sciences. Whilst introductory statistics courses cover essential techniques, the complexities of behaviour demand that more flexible and comprehensive methods are also employed. Analysis of Variance (ANOVA) has become one of the most common of these and it is therefore essential for both student and researcher to have a thorough understanding of it.A Student's Guide to Analysis of Variance covers a range of statistical techniques associated with ANOVA, including single and multiple factor designs, various follow-up procedures such as post-hoc tests, and how to make sense of interactions. Suggestions on the best use of techniques and advice on how to avoid the pitfalls are included, along with guidelines on the writing of formal reports.Introductory level topics such as standard deviation, standard error and t-tests are revised, making this book an invaluable aid to all students for whom ANOVA is a compulsory topic. It will also serve as a useful refresher for the more advanced student and practising researcher.