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2005-04-14

Research Design and Statistical Analysis by Jerome L. Myers, Arnold D. Well

List Price: $79.95

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  • 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 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. 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--Two early chapters are now largely devoted to examples and discussion of displays of data and there are more graphs throughout.
    • Confidence Intervals--Now 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 (ch.6) 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 (ch. 3) and with an increased emphasis on the most frequent misinterpretations made when using these analyses.
    • Real Data Sets--Includes a FREE CD, that contains several artificial data sets used in the book in SPSS, SYSTAT, and ASCII formats. An Instructor's Solutions Manual, containing the intermediate steps to all of the text exercises, is available free to adopters.

    [此贴子已经被作者于2005-8-1 23:26:54编辑过]

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    2005-4-14 07:45:00

    Contents

    • Preface.
    • Introduction.
    • Looking at Data: Univariate Distributions.
    • Variables.
    • Probability and the Binomial Distribution.
    • Estimation and Hypothesis Tests: The Normal Distribution.
    • Estimation, Hypothesis Tests, and Effect Size: The t Distribution.
    • The Chi Square and F Distributions.
    • Between Subjects Designs: One Factor.
    • Contrasts Among Means.
    • Trend Analysis. Multifactor Between-Subjects Designs: Significance Tests in the Two-Way Case.
    • Multifactor Between-Subjects Designs: Further Developments.
    • Repeated-Measures Designs.
    • Mixed Designs: Between-Subjects and Within-Subjects Factors.
    • Using Concomitant Variables to Increase Power: Blocking and Analysis of Covariance.
    • Hierarchical Designs.
    • Latin Squares and Related Designs.
    • More About Correlation.
    • More About Bivariate Regression.
    • Multiple Regression.
    • Regression With Categorical and Quantitative Variables: The General Linear Model.
    • Appendices: Notation and Summation Operations.
    • Expected Values and Their Applications.
    • Statistical Tables.
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    2005-4-14 07:45:00

    Testimonials:

    "... the authors do a masterful job of presenting important concepts in a rigorous but accessible manner. They do not try to cover everything and leave students without any guidelines for selecting appropriate designs and procedures. Rather, where recommendations are appropriate, they make them and explain their reasoning. Where specific recommendations are not possible, they discuss the issues relevant to choice of design or statistics in order that students will learn to make their own decisions in a thoughtful way. A masterful teaching job." -- Dr. Robert Lorch University of Kentucky

    "The Wilkinson paper is the state of the art in APA thinking. It is nice to see a textbook attempt to incorporate these changes so fast into student learning. The emphasis on statistical power and effect size is very timely." -- Dr. Jay Maddock University of Hawaii at Manoa

    "One of the primary changes is that the authors include examples from real data sets. In contrast to most books, which rely on 'created' data sets, this provides a framework for talking about the complications of messy data. I have been using the current edition to teach for the past five years, and I find that it provides me with the basis for a terrific class." -- Dr. Celia Klin Binghamton University

    "Nobody else presents the level of sophistication with the clarity that Myers does.I think this book can serve as the primary design and analysis book for a variety of graduate programs other than psychology, such as communication disorders, education, and any other discipline where empirical research is required for a master's degree." -- Dr. Thomas Petros University of North Dakota

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    2005-4-14 14:00:00
    That is a good and useful book. Thanks.
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    2005-4-17 02:09:00
    where is it????????
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    2005-5-2 02:37:00
    提示: 作者被禁止或删除 内容自动屏蔽
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