Design and Analysis: A Researcher's HandbookThe fourth edition of "Design and Analysis" continues to offer a readily accessible introduction to the designed experiment in research and the statistical analysis of the data from such experiments. Unique because it emphasizes the use of analytical procedures, this book is appropriate for all as it requires knowledge of only the most fundamental mathematical skills and little or no formal statistical background. Topics include: single- and two-factor designs with independent groups of subjects; corresponding designs with multiple observations; analysis of designs with unequal sample sizes; analysis of covariance; designs with three factors, including all combinations of between-subjects and within-subject factors; random factors and statistical generalization; and nested factors. This book lives up to its name as a handbook, because of its usefulness as a source and guide to researchers who require assistance in both planning a study and analyzing its results. |
Contents
An Overview of the Research Enterprise The Role of Statistics in the Behavioral Sciences | 12 |
SINGLEFACTOR EXPERIMENTS | 19 |
Control by Randomization An Index for the Evaluation of Treatment Effects | 33 |
Copyright | |
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Common terms and phrases
a₁ a₂ AB matrix ABC matrix adjusted analysis of covariance analysis of variance assumptions Bcomp blocking calculations cell means Chapter coefficients column combination Comp comparisons involving completely randomized design computational formulas conducted consider contrast control variable df statement dfs/A discussed effect of factor equal error variance estimate evaluated EW error rate F distribution F ratio F test factorial experiment given indicates interaction effects levels of factor linear listed MSS/AB multiple comparisons null hypothesis number of observations number of subjects Numerical Example obtained orthogonal orthogonal polynomials particular population procedure quadratic quantity random independent variables regression repeated-measures design represented Scheffé test significant simple main effects single-factor experiment sources of variance specific SS Acomp statistical sums of squares three-way interaction total number treatment conditions treatment effects treatment groups treatment means trend components Tukey two-way interactions type I error weighted means