About this book
This text provides undergraduate students with a practical introduction to the design and analysis of experiments, particularly in the social and behavioral sciences. Its straight forward approach, step-by-step descriptions, worked examples, and exercises should combine to make important concepts and methods more accessible to readers of diverse backgrounds.
For its second edition the book has been revised to give a clearer understanding of how experiments are designed and how the results are interpreted. It features: a new chapter on estimation procedures; a new chapter on the analysis of two-factor within-subjects design; a new chapter combining discussions of type I, II, and cumulative type I errors with expanded coverage of error control and sample size; a revised discussion of linear correlation and regression; expanded discussions of the analysis of experiments with more detailed examinations of power and effect size and additional problems and exercises, some with detailed answers provided in an appendix.
Part 1 Experimenta l design and preliminary data analysis: introduction to experimental design - getting started, how do psychologists conduct research?, experimental research design, summary, exercises; preliminary data analysis - the mean as a measure of central tendency, the variance as a measure of variability, additional descriptive techniques, summary, exercises. Part 2 The analysis of single-factor experiments: the logic of hypothesis testing - neutralizing nuisance variables through randomization, index of the treatment effects, hypothesis testing, summary, exercises; calculating the F ratio - design and notation, partitioning the total sum of squares, sums of squares - computational formulas, the analysis of variance, summary, exercises; evaluating the F ratio - the sampling distribution of F, determining the critical value of F, forming the decision rule, assumptions underlying the analysis, a complete numerical example, special analysis with two treatment conditions, summary, exercises, appendix: an explanation of the correction for unequal variances; analytical comparisons in the single-factor design - the nature of analytical comparisons, an example of the relationship between research hypotheses and analytical comparisons, analyzing differences between pairs of means, more complex analytical comparisons, summary, exercises, appendix: using the t test to analyze single-df comparisons; estimating population means and effect size - interval estimation in experiments, the magnitude of treatment effects, summary, exercises; errors of hypothesis testing and statistical power - statistical errors in hypothesis testing, cumulative type 1 error, using power to estimate sample size, summary, exercises, appendix: an alternative method for estimating sample size. Part 3 The analysis of factorial designs: introduction to the analysis of factorial experiments - the factorial experiment, main effects and interaction, identifying basic deviations, the analysis of variance, calculating sums of squares, a numerical example, summary, exercises; analytical comparisons in the factorial design - interpreting F tests in the factorial design, the detailed analysis of main effects, analyzing simple effects, analyzing simple comparisons, an overall plan of analysis, summary, exercises, appendix: analyzing interaction contrasts. Part 4 The analysis of within-subjects designs: the single-factor within-subjects design - reducing error variance, logic of the analysis of within-subjects designs, computational formulas for the analysis of variance, a numerical example, analytical comparisons, planning within-subjects designs, summary, exercises, appendix: using separate error terms to evaluate analytical comparisons; the mixed within-subjects factorial design - a comparison of factorial designs, the logic of the analysis, analysis of variance, a numerical example, analytical comparisons, summary, exercises; part contents.