Research Design and Statistical Analysis / Edition 1

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Overview

Intended both as a textbook for students and as a resource for researchers, this book emphasizes the statistical concepts and assumptions necessary to describe and make inferences about real data. Throughout the book the authors encourage readers to plot and examine their data find confidence intervals, use power analyses to determine sample size, and calculate effect sizes.

Using an intuitive, informal style, the authors adopt a "bottom-up" approach - a simpler, less abstract discussion of analysis of variance is presented prior to developing the more general model. A concern for alternatives to standard analyses allows for the integration of non-parametric techniques into relevant design chapter, rather than in a single, isolated chapter. This organization allows for the comparison of the pros and cons of alternative procedures within the research context to which they apply.

Basic concepts such as sampling distribution, expected mean squares, design efficiency, and statistical models are emphasized throughout. This approach provides a stronger conceptual foundation in order to help readers generalize the concepts to new situations they will encounter in their research and to better understand the advice of statistical consultants and the content of article using statistical methodology.

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Product Details

  • ISBN-13: 9780673464149
  • Publisher: Addison-Wesley Educational Publishers, Inc.
  • Publication date: 3/28/1991
  • Edition number: 1
  • Pages: 600

Table of Contents

Preface
Ch. 1 Introduction 1
Ch. 2 Looking at Data: Univariate Distributions 10
Ch. 3 Looking at Data: Relations Between Quantitative Variables 37
Ch. 4 Probability and the Binomial Distribution 61
Ch. 5 Estimation and Hypothesis Tests: The Normal Distribution 100
Ch. 6 Estimation, Hypothesis Tests, and Effect Size: The t Distribution 140
Ch. 7 The Chi-Square and F Distributions 173
Ch. 8 Between-Subjects Designs: One Factor 191
Ch. 9 Contrasts Among Means 233
Ch. 10 Trend Analysis 267
Ch. 11 Multifactor Between-Subjects Designs: Significance Tests in the Two-Way Case 284
Ch. 12 Multifactor Between-Subjects Designs: Further Developments 315
Ch. 13 Repeated-Measures Designs 342
Ch. 14 Mixed Designs: Between-Subjects and Within-Subjects Factors 386
Ch. 15 Using Concomitant Variables to Increase Power: Blocking and Analysis of Covariance 412
Ch. 16 Hierarchical Designs 436
Ch. 17 Latin Squares and Related Designs 457
Ch. 18 More About Correlation 480
Ch. 19 More About Bivariate Regression 519
Ch. 20 Multiple Regression 562
Ch. 21 Regression with Categorical and Quantitative Variables: The General Linear Model 614
App. A Notation and Summation Operations 641
App. B Expected Values and Their Applications 649
App. C: Statistical Tables 653
Answers to Selected Exercises 685
Endnotes 721
References 729
Author Index 743
Subject Index 749
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