Summary

This comprehensive, flexible text is used in both one- and two-semester courses to review introductory through intermediate statistics. Instructors select the topics that are most appropriate for their course. Its conceptual approach helps students more easily understand the concepts and interpret SPSS and research results. Key concepts are simply stated and occasionally reintroduced and related to one another for reinforcement. Numerous examples demonstrate their relevance. This edition features more explanation to increase understanding of the concepts. Only crucial equations are included. In addition to updating throughout, the new edition features: New co-author, Debbie L. Hahs-Vaughn, the 2007 recipient of the University of Central Florida's College of Education Excellence in Graduate Teaching Award. A new chapter on logistic regression models for today's more complex methodologies. More on computing confidence intervals and conducting power analyses using G*Power. Many more SPSS screenshots to assist with understanding how to navigate SPSS and annotated SPSS output to assist in the interpretation of results. Extended sections on how to write-up statistical results in APA format. New learning tools including chapter-opening vignettes, outlines, and a list of key concepts, many more examples, tables, and figures, boxes, and chapter summaries. More tables of assumptions and the effects of their violation including how to test them in SPSS. 33% new conceptual, computational, and all new interpretative problems. A website that features Power Points, answers to the even-numbered problems, and test items for instructors, and for students the chapter outlines, key concepts, and datasets that can be used in SPSS and other packages, and more. Each chapter begins with an outline, a list of key concepts, and a vignette related to those concepts. Realistic examples from education and the behavioral sciences illustrate those concepts. Each example examines the procedures and assumptions and provides instructions for how to run SPSS, including annotated output, and tips to develop an APA style write-up. Useful tables of assumptions and the effects of their violation are included, along with how to test assumptions in SPSS. Stop and Think Boxes provide helpful tips for better understanding the concepts. Each chapter includes computational, conceptual, and interpretive problems. The data sets used in the examples and problems are provided on the web. Answers to the odd-numbered problems are given in the book. The first five chapters review descriptive statistics including ways of representing data graphically, statistical measures, the normal distribution, and probability and sampling. The remainder of the text covers inferential statistics involving means, proportions, variances, and correlations, basic and advanced analysis of variance and regression models. Topics not dealt with in other texts such as robust methods, multiple comparison and nonparametric procedures, and advanced ANOVA and multiple and logistic regression models are also reviewed. Intended for one- or two-semester courses in statistics taught in education and/or the behavioral sciences at the graduate and/or advanced undergraduate level, a prerequisite in statistics is not assumed. A rudimentary knowledge of algebra is required.

Preface	p. xiii
Acknowledgments	p. xvii
Introduction	p. 1
What Is the Value of Statistics?	p. 3
Brief Introduction to History of Statistics	p. 4
General Statistical Definitions	p. 5
Types of Variables	p. 7
Scales of Measurement	p. 8
Summary	p. 13
Problems	p. 14
Data Representation	p. 17
Tabular Display of Distributions	p. 18
Graphical Display of Distributions	p. 23
Percentiles	p. 29
SPSS	p. 33
Templates for Research Questions and APA-Style Paragraph	p. 41
Summary	p. 42
Problems	p. 43
Univariate Population Parameters and Sample Statistics	p. 49
Summation Notation	p. 50
Measures of Central Tendency	p. 51
Measures of Dispersion	p. 56
SPSS	p. 65
Templates for Research Questions and APA-Style Paragraph	p. 69
Summary	p. 70
Problems	p. 71
Normal Distribution and Standard Scores	p. 77
Normal Distribution	p. 78
Standard Scores	p. 84
Skewness and Kurtosis Statistics	p. 87
SPSS	p. 91
Templates for Research Questions and APA-Style Paragraph	p. 98
Summary	p. 99
Problems	p. 99
Introduction to Probability and Sample Statistics	p. 105
Brief Introduction to Probability	p. 106
Sampling and Estimation	p. 109
Summary	p. 117
Appendix: Probability That at Least Two Individuals Have the Same Birthday	p. 117
Problems	p. 118
Introduction to Hypothesis Testing: Inferences About a Single Mean	p. 121
Types of Hypotheses	p. 122
Types of Decision Errors	p. 124
Level of Significance (¿)	p. 127
Overview of Steps in Decision-Making Process	p. 129
Inferences About ¿ When ¿ Is Known	p. 130
Type II Error (ß) and Power (1-ß)	p. 134
Statistical Versus Practical Significance	p. 138
Inferences About ¿ When ¿ Is Unknown	p. 139
SPSS	p. 145
G*Power	p. 149
Template and APA-Style Write-Up	p. 155
Summary	p. 156
Problems	p. 157
Inferences About the Difference Between Two Means	p. 163
New Concepts	p. 164
Inferences About Two Independent Means	p. 166
Inferences About Two Dependent Means	p. 176
SPSS	p. 180
G&Power	p. 192
Template and APA-Style Write-Up	p. 195
Summary	p. 198
Problems	p. 198
Inferences About Proportions	p. 205
Inferences About Proportions Involving Normal Distribution	p. 206
Inferences About Proportions Involving Chi-Square Distribution	p. 217
SPSS	p. 224
G*Power	p. 231
Template and APA-Style Write-Up	p. 234
Summary	p. 236
Problems	p. 237
Inferences About Variances	p. 241
New Concepts	p. 242
Inferences About Single Variance	p. 244
Inferences About Two Dependent Variances	p. 246
Inferences About Two or More Independent Variances (Homogeneity of Variance Tests)	p. 248
SPSS	p. 252
Template and APA-Style Write-Up	p. 253
Summary	p. 253
Problems	p. 254
Bivariate Measures of Association	p. 259
Scatterplot	p. 260
Covariance	p. 263
Pearson Product-Moment Correlation Coefficient	p. 265
Inferences About Pearson Product-Moment Correlation Coefficient	p. 266
Assumptions and Issues Regarding Correlations	p. 269
Other Measures of Association	p. 272
SPSS	p. 276
G*Power	p. 283
Template and APA-Style Write-Up	p. 286
Summary	p. 287
Problems	p. 287
One-Factor Analysis of Variance: Fixed-Effects Model	p. 291
Characteristics of One-Factor ANOVA Model	p. 292
Layout of Data	p. 296
ANOVA Theory	p. 296
ANOVA Model	p. 302
Assumptions and Violation of Assumptions	p. 309
Unequal n's or Unbalanced Procedure	p. 312
Alternative ANOVA Procedures	p. 312
SPSS and G*Power	p. 313
Template and APA-Style Write-Up	p. 334
Summary	p. 336
Problems	p. 336
Multiple Comparison Procedures	p. 341
Concepts of Multiple Comparison Procedures	p. 342
Selected Multiple Comparison Procedures	p. 348
SPSS	p. 362
Template and APA-Style Write-Up	p. 366
Summary	p. 366
Problems	p. 367
Factorial Analysis of Variance: Fixed-Effects Model	p. 371
Two-Factor ANOVA Model	p. 372
Three-Factor and Higher-Order ANOVA	p. 390
Factorial ANOVA With Unequal n's	p. 393
SPSS and G*Power	p. 395
Template and APA-Style Write-Up	p. 417
Summary	p. 419
Problems	p. 420
Introduction to Analysis of Covariance: One-Factor Fixed-Effects Model With Single Covariate	p. 427
Characteristics of the Model	p. 428
Layout of Data	p. 431
ANCOVA Model	p. 431
ANCOVA Summary Table	p. 432
Partitioning the Sums of Squares	p. 433
Adjusted Means and Related Procedures	p. 434
Assumptions and Violation of Assumptions	p. 436
Example	p. 441
ANCOVA Without Randomization	p. 443
More Complex ANCOVA Models	p. 444
Nonparametric ANCOVA Procedures	p. 444
SPSS and G*Power	p. 445
Template and APA-Style Paragraph	p. 469
Summary	p. 471
Problems	p. 471
Random- and Mixed-Effects Analysis of Variance Models	p. 477
One-Factor Random-Effects Model	p. 478
Two-Factor Random-Effects Model	p. 483
Two-Factor Mixed-Effects Model	p. 488
One-Factor Repeated Measures Design	p. 493
Two-Factor Split-Plot or Mixed Design	p. 500
SPSS and G*Power	p. 508
Template and APA-Style Write-Up	p. 548
Summary	p. 551
Problems	p. 551
Hierarchical and Randomized Block Analysis of Variance Models	p. 557
Two-Factor Hierarchical Model	p. 558
Two-Factor Randomized Block Design for n = 1	p. 566
Two-Factor Randomized Block Design for n > 1	p. 574
Friedman Test	p. 574
Comparison of Various ANOVA Models	p. 575
SPSS	p. 576
Template and APA-Style Write-Up	p. 603
Summary	p. 605
Problems	p. 605
Simple Linear Regression	p. 611
Concepts of Simple Linear Regression	p. 612
Population Simple Linear Regression Model	p. 614
Sample Simple Linear Regression Model	p. 615
SPSS	p. 634
G*Power	p. 647
Template and APA-Style Write-Up	p. 650
Summary	p. 652
Problems	p. 652
Multiple Regression	p. 657
Partial and Semipartial Correlations	p. 658
Multiple Linear Regression	p. 661
Methods of Entering Predictors	p. 676
Nonlinear Relationships	p. 679
Interactions	p. 680
Categorical Predictors	p. 680
SPSS	p. 682
G*Power	p. 698
Template and APA-Style Write-Up	p. 701
Summary	p. 703
Problems	p. 704
Logistic Regression	p. 709
How Logistic Regression Works	p. 710
Logistic Regression Equation	p. 711
Estimation and Model Fit	p. 715
Significance Tests	p. 716
Assumptions and Conditions	p. 721
Effect Size	p. 725
Methods of Predictor Entry	p. 726
SPSS	p. 727
G*Power	p. 746
Template and APA-Style Write-Up	p. 749
What Is Next?	p. 751
Summary	p. 752
Problems	p. 752
Appendix: Tables	p. 783
References	p. 783
Odd-Numbered Answers to Problems	p. 793
Author Index	p. 809
Subject Index	p. 813
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