Foundations of Behavioral Statistics : An Insight-Based Approach

by Thompson, Bruce

Edition: 1st

ISBN13: 9781593858407

ISBN10: 159385840X

Format: Paperback

Pub. Date: 2008-02-26

Publisher(s): The Guilford Press

Other versions by this Author

List Price: ~~$71.46~~

Rent Textbook

Select for Price

Add to Cart

There was a problem. Please try again later.

New Textbook

We're Sorry
Sold Out

Used Textbook

We're Sorry
Sold Out

eTextbook

We're Sorry
Not Available

Buy from our Marketplace starting at $5.50

Summary

With humor, extraordinary clarity, and carefully paced explanations and examples, Bruce Thompson shows readers how to use the latest techniques for interpreting research outcomes as well as how to make statistical decisions that result in better research. Utilizing the general linear model to demonstrate how different statistical methods are related to each other, Thompson integrates a broad array of methods involving only a single dependent variable, ranging from classical and robust location descriptive statistics, through effect sizes, and on through ANOVA, multiple regression, loglinear analysis and logistic regression. Special features include SPSS and Excel demonstrations that offer opportunities, in the book's datasets and on Thompson's website, for further exploration of statistical dynamics.

Author Biography

Bruce Thompson is Distinguished Professor of Educational Psychology and Distinguished Professor of Library Sciences, Texas A&M University, and Adjunct Professor of Family and Community Medicine, Baylor College of Medicine, Houston. He is the coeditor of the teaching, learning, and human development section of the American Educational Research Journal and past editor of Educational and Psychological Measurement, the series Advances in Social Science Methodology, and two other journals. He is the author or editor of 10 books, has written over 175 research articles, and has made contributions that have been influential in promoting greater emphasis on effect size reporting and interpretation, and improved understanding of score reliability.

Introductory Terms and Concepts	p. 1
Definitions of Some Basic Terms	p. 3
Levels of Scale	p. 13
Some Experimental Design Considerations	p. 24
Some Key Concepts	p. 30
Reflection Problems	p. 30
Location	p. 31
Reasonable Expectations for Statistics	p. 32
Location Concepts	p. 33
Three Classical Location Descriptive Statistics	p. 36
Four Criteria for Evaluating Statistics	p. 46
Two Robust Location Statistics	p. 47
Some Key Concepts	p. 49
Reflection Problems	p. 49
Dispersion	p. 53
Quality of Location Descriptive Statistics	p. 54
Important in Its Own Right	p. 54
Measures of Score Spread	p. 57
Variance	p. 62
Situation-Specific Maximum Dispersion	p. 67
Robust Dispersion Descriptive Statistics	p. 69
Standardized Score World	p. 70
Some Key Concepts	p. 72
Reflection Problems	p. 73
Shape	p. 75
Two Shape Descriptive Statistics	p. 76
Normal Distributions	p. 86
Two Additional Univariate Graphics	p. 91
Some Key Concepts	p. 94
Reflection Problems	p. 95
Bivariate Relationships	p. 97
Pearson's r	p. 99
Three Features of r	p. 101
Three Interpretation Contextual Factors	p. 110
Psychometrics of the Pearson r	p. 116
Spearman's rho	p. 118
Two Other r-Equivalent Correlation Coefficients	p. 124
Bivariate Normality	p. 128
Some Key Concepts	p. 130
Reflection Problems	p. 131
Statistical Significance	p. 133
Sampling Distributions	p. 135
Hypothesis Testing	p. 142
Properties of Sampling Distributions	p. 150
Standard Error/Sampling Error	p. 154
Test Statistics	p. 156
Statistical Precision and Power	p. 169
Pcalculated	p. 177
Some Key Concepts	p. 182
Reflection Problems	p. 182
Practical Significance	p. 185
Effect Sizes	p. 187
Confidence Intervals	p. 200
Confidence Intervals for Effect Sizes	p. 207
Some Key Concepts	p. 210
Reflection Problems	p. 211
Multiple Regression Analysis: Basic GLM Concepts	p. 215
Purposes of Regression	p. 217
Simple Linear Prediction	p. 220
Perfectly Uncorrelated Predictors	p. 232
Correlated Predictors, No Suppressor Effects	p. 234
Correlated Predictors, Suppressor Effects Present	p. 237
[beta] Weights versus Structure Coefficients	p. 240
A Final Comment on Collinearity	p. 244
Some Key Concepts	p. 245
Reflection Problems	p. 246
A GLM Interpretation Rubric	p. 247
Do I Have Anything?	p. 248
Where Does My Something Originate?	p. 266
Stepwise Methods	p. 270
Invoking Some Alternative Models	p. 278
Some Key Concepts	p. 299
Reflection Problems	p. 300
One-Way Analysis of Variance (ANOVA)	p. 303
Experimentwise Type I Error	p. 304
ANOVA Terminology	p. 309
The Logic of Analysis of Variance	p. 311
Practical and Statistical Significance	p. 317
The "Homogeneity of Variance" Assumption	p. 319
Post Hoc Tests	p. 325
Some Key Concepts	p. 329
Reflection Problems	p. 330
Multiway and Other Alternative ANOVA Models	p. 333
Multiway Models	p. 333
Factorial versus Nonfactorial Analyses	p. 343
Fixed-, Random-, and Mixed-Effects Models	p. 345
Brief Comment on ANCOVA	p. 354
Some Key Concepts	p. 357
Reflection Problems	p. 358
The General Linear Model (GLM): ANOVA via Regression	p. 359
Planned Contrasts	p. 360
Trend/Polynomial Planned Contrasts	p. 375
Repeated-Measures ANOVA via Regression	p. 380
GLM Lessons	p. 385
Some Key Concepts	p. 390
Reflection Problems	p. 391
Some Logistic Models: Model Fitting in a Logistic Context	p. 393
Logistic Regression	p. 394
Loglinear Analysis	p. 413
Some Key Concepts	p. 423
Reflection Problems	p. 424
Scores (n = 100) with Near Normal Distributions	p. 427
References	p. 431
Index	p. 449
About the Author	p. 457
Table of Contents provided by Ingram. All Rights Reserved.