Design and analysis: a researcher's handbook
The 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.
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An Overview of the Research Enterprise The Role of Statistics in the Behavioral Sciences
Control by Randomization An Index for the Evaluation of Treatment Effects
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ABC matrix adjusted analysis of covariance analysis of variance assumptions blocking calculations cell means Chapter column Comp comparisons involving completely randomized design computational formulas conducted consider contrast control variable df associated df statement discussed effect of factor equal error variance estimate evaluated EW error rate F distribution F ratio F test factorial experiment given indicates levels of factor linear listed MSSIAB multiple comparisons nested factor null hypothesis number of observations number of subjects Numerical Example obtained orthogonal polynomials particular population portion of Table post-hoc comparisons procedure quadratic quantity random independent variables regression repeated factors repeated-measures design represented Scheffe test significant simple main effects single-factor experiment sources of variance specific statistical sums of squares task three-way interaction total number treatment conditions treatment effects treatment groups treatment means trend components Tukey two-factor two-way interactions type I error weighted means within-groups mean square x B interaction