Research Design & Statistical Analysis - Hardcover

This book emphasizes the statistical concepts and assumptions necessary to describe and make inferences about real data. Throughout the book the authors encourage the reader to plot and examine their data, find confidence intervals, use power analyses to determine sample size, and calculate effect sizes. The goal is to ensure the reader understands the underlying logic and assumptions of the analysis and what it tells them, the limitations of the analysis, and the possible consequences of violating assumptions.

The 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 chapters, 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 distributions, expected mean squares, design efficiency, and statistical models are emphasized throughout. This approach provides a stronger conceptual foundation in order to help the reader 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 articles using statistical methodology.

The second edition features a greater emphasis on graphics, confidence intervals, measures of effect size, power analysis, tests of contrasts, elementary probability, correlation, and regression. A Free CD that contains several real and artificial data sets used in the book in SPSS, SYSTAT, and ASCII formats, is included in the back of the book. An Instructor's Solutions Manual, containing the intermediate steps to all of the text exercises, is available free to adopters.

Intended both as a textbook for students and as a resource for researchers, this volume emphasizes the statistical concepts and assumptions necessary to describe and make inferences about real data. Throughout the text the authors encourage the reader to plot and examine their data, find confidence intervals, use power analyses to determine sample size, and calculate effect sizes. The goal is to ensure the reader understands: the underlying logic and assumptions of the analysis and what it tells them; the limitations of the analysis; and the possible consequences of violating assumptions. 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 chapters, 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. This second edition features a greater emphasis on: graphics - two early chapters are now largely devoted to examples and discussion of displays of data and there are more graphs throughout; confidence intervals - now are usually presented before hypothesis tests to help focus on the question "What is the size of the effect?" rather than "Is there an effect?"; measures of effect size - now are introduced earlier, in the context of the t test, and then are routinely discussed in a variety of research designs and analyses; power analysis - computer programs are now used to illustrate the calculation of power; tests of contrasts - now are introduced earlier as extensions of the usual two-sample t tests in order to simplify the discussion; elementary probability - a new chapter on basic probability serves as a review and a means for using the binomial distribution to introduce hypothesis testing; correlation and regression - now introduced earlier and with an increased emphasis on the most frequent misinterpretations made when using these analyses; real data sets - a free CD contains several real and artificial data sets used in the book in SPSS, SYSTAT, and ASCII formats.