Foundations of Behavioral Statistics: An Insight-Based Approach

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April 2006



Using humor, extraordinary clarity, and carefully paced explanations and examples, Thompson leads readers to the cutting edge of interpreting research outcomes and teaches how to make the statistical decisions that result in better research.


Preface. Introductory Terms and Concepts. Definitions of Some Basic Terms. Levels of Scale. Some Experimental Design Considerations. Some Key Concepts. Reflection Problems. Location. Location Concepts. Three Classical Location Descriptive Statistics. Four Criteria for Evaluating Statistics. Two Robust Location Statistics. Some Key Concepts. Reflection Problems. Dispersion. Measures of Score Spread. Situation-Specific Maximum Dispersion. Robust Dispersion Descriptive Statistics. Standardized Score World. Some Key Concepts. Reflection Problems. Shape. Two Shape Descriptive Statistics. Normal Distributions. Two Additional Univariate Graphics. Some Key Concepts. Reflection Problems. Bivariate Relationship. Pearson's r. Three Features of r. Three Interpretation Contextual Factors. Psychometrics of the Pearson r. Spearman's rho. Two Other r -Equivalent Correlation Coefficients. Bivariate Normality. Some Key Concepts. Reflection Problems. Statistical Significance. Sampling Distributions. Hypothesis Testing. Properties of Sampling Distributions. Standard Error/Sampling Error. Test Statistics. Statistical Precision and Power. pCALCULATED. Some Key Concepts. Reflection Problems. Practical Significance. Effect Sizes. Confidence Intervals. Confidence Intervals for Effect Sizes. Some Key Concepts. Reflection Problems. Multiple Regression Analysis: Basic GLM Concepts. Purposes of Regression. Simple Linear Prediction. Case #1: Perfectly Uncorrelated Predictors. Case #2: Correlated Predictors, No Suppressor Effects. Case #3: Correlated Predictors, Suppressor Effects Present. b Weights versus Structure Coefficients. A Final Comment on Collinearity. Some Key Concepts. Reflection Problems. A GLM Interpretation Rubric. Do I Have Anything? Where Does My Something Originate? Stepwise Methods. Invoking Some Alternative Models. Some Key Concepts. Reflection Problems. One-way Analysis of Variance (ANOVA). Experimentwise Type I Error. ANOVA Terminology. The Logic of Analysis of Variance. Practical and Statistical Significance. The "Homogeneity of Variance" Assumption. Post Hoc Tests. Some Key Concepts. Reflection Problems. Multiway and Alternative ANOVA Models. Multiway Models. Factorial versus Nonfactorial Analyses. Fixed-, Random-, and Mixed-Effects Models. Brief Comment on ANCOVA. Some Key Concepts. Reflection Problems. The General Linear Model (GLM): ANOVA via Regression. Planned Contrasts. Trend/Polynomial Planned Contrasts. Repeated Measures ANOVA via Regression. GLM Lessons. Some Key Concepts. Reflection Problems. Some Logistic Models: Model Fitting in a Logistic Context. Logistic Regression. Loglinear Analysis. Some Key Concepts. Reflection Problems. Appendix: Scores (n = 100) with Near Normal Distributions.


Bruce Thompson, Department of Educational Psychology, Texas A&M University, College Station, TX


'An important contribution to improving data analysis and interpretation methods in the social sciences. This book treats many important topics that are ignored in most statistics books... The Statistical Significance chapter is excellent and one of the crown jewels of this book. This is the kind of understanding of significance testing that we should seek to impart to students and researchers. No other stat book, to my knowledge, has a chapter like this one. This is the direction in which things are moving today.' - Frank L. Schmidt, College of Business, University of Iowa 'This book would be suited for professional and/or class use. The benefit for professional use is the vast number of resources and references cited throughout. This wealth of seminal works from some of the best minds in the field of statistics would provide professionals with supplemental knowledge and information on many crucial statistical issues that have recently been proposed, debated, challenged, and mandated (APA).' - Victoria Rodlin, Statistical Consultant (former faculty, Department of Psychology, California State University, Fullerton) 'This is an outstanding text that represents a new era in the learning and reporting of statistics in the behavioral sciences. Thompson focuses on analytic thinking rather than mathematical number-crunching, unlike others that emphasize calculations at the expense of critical thinking. The use of humor throughout the book is also a distinctive feature and it brings a considerable amount of 'realism' to the text. This book is at the leading edge of methodological advances regarding the interpretation of research outcomes, and will serve a critical role in the continued evolution of the behavioral statistics field.' - Robin K. Henson, Department of Technology and Cognition, University of North Texas 'This text has a clear and logical approach that allows its use across a variety of fields and levels of instruction.' - Kirk E. Wheeler, Indiana University School of Nursing 'This the best book for graduate students in statistics, due to the clarity and simplicity of the exposition.' - Pedro Reyes, Department of Educational Administration, University of Texas at Austin
EAN: 9781593852856
ISBN: 1593852851
Untertitel: Sprache: Englisch.
Erscheinungsdatum: April 2006
Seitenanzahl: 457 Seiten
Format: gebunden
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