An Introduction to Statistical Concepts: Third Edition

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  • Edition: 3rd
  • Format: Hardcover
  • Copyright: 2012-03-01
  • Publisher: Routledge/Psych
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Supplemental Materials

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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.

Table of Contents

Prefacep. xiii
Acknowledgmentsp. xvii
Introductionp. 1
What Is the Value of Statistics?p. 3
Brief Introduction to History of Statisticsp. 4
General Statistical Definitionsp. 5
Types of Variablesp. 7
Scales of Measurementp. 8
Summaryp. 13
Problemsp. 14
Data Representationp. 17
Tabular Display of Distributionsp. 18
Graphical Display of Distributionsp. 23
Percentilesp. 29
SPSSp. 33
Templates for Research Questions and APA-Style Paragraphp. 41
Summaryp. 42
Problemsp. 43
Univariate Population Parameters and Sample Statisticsp. 49
Summation Notationp. 50
Measures of Central Tendencyp. 51
Measures of Dispersionp. 56
SPSSp. 65
Templates for Research Questions and APA-Style Paragraphp. 69
Summaryp. 70
Problemsp. 71
Normal Distribution and Standard Scoresp. 77
Normal Distributionp. 78
Standard Scoresp. 84
Skewness and Kurtosis Statisticsp. 87
SPSSp. 91
Templates for Research Questions and APA-Style Paragraphp. 98
Summaryp. 99
Problemsp. 99
Introduction to Probability and Sample Statisticsp. 105
Brief Introduction to Probabilityp. 106
Sampling and Estimationp. 109
Summaryp. 117
Appendix: Probability That at Least Two Individuals Have the Same Birthdayp. 117
Problemsp. 118
Introduction to Hypothesis Testing: Inferences About a Single Meanp. 121
Types of Hypothesesp. 122
Types of Decision Errorsp. 124
Level of Significance ()p. 127
Overview of Steps in Decision-Making Processp. 129
Inferences About When Is Knownp. 130
Type II Error () and Power (1-)p. 134
Statistical Versus Practical Significancep. 138
Inferences About When Is Unknownp. 139
SPSSp. 145
G*Powerp. 149
Template and APA-Style Write-Upp. 155
Summaryp. 156
Problemsp. 157
Inferences About the Difference Between Two Meansp. 163
New Conceptsp. 164
Inferences About Two Independent Meansp. 166
Inferences About Two Dependent Meansp. 176
SPSSp. 180
G&Powerp. 192
Template and APA-Style Write-Upp. 195
Summaryp. 198
Problemsp. 198
Inferences About Proportionsp. 205
Inferences About Proportions Involving Normal Distributionp. 206
Inferences About Proportions Involving Chi-Square Distributionp. 217
SPSSp. 224
G*Powerp. 231
Template and APA-Style Write-Upp. 234
Summaryp. 236
Problemsp. 237
Inferences About Variancesp. 241
New Conceptsp. 242
Inferences About Single Variancep. 244
Inferences About Two Dependent Variancesp. 246
Inferences About Two or More Independent Variances (Homogeneity of Variance Tests)p. 248
SPSSp. 252
Template and APA-Style Write-Upp. 253
Summaryp. 253
Problemsp. 254
Bivariate Measures of Associationp. 259
Scatterplotp. 260
Covariancep. 263
Pearson Product-Moment Correlation Coefficientp. 265
Inferences About Pearson Product-Moment Correlation Coefficientp. 266
Assumptions and Issues Regarding Correlationsp. 269
Other Measures of Associationp. 272
SPSSp. 276
G*Powerp. 283
Template and APA-Style Write-Upp. 286
Summaryp. 287
Problemsp. 287
One-Factor Analysis of Variance: Fixed-Effects Modelp. 291
Characteristics of One-Factor ANOVA Modelp. 292
Layout of Datap. 296
ANOVA Theoryp. 296
ANOVA Modelp. 302
Assumptions and Violation of Assumptionsp. 309
Unequal n's or Unbalanced Procedurep. 312
Alternative ANOVA Proceduresp. 312
SPSS and G*Powerp. 313
Template and APA-Style Write-Upp. 334
Summaryp. 336
Problemsp. 336
Multiple Comparison Proceduresp. 341
Concepts of Multiple Comparison Proceduresp. 342
Selected Multiple Comparison Proceduresp. 348
SPSSp. 362
Template and APA-Style Write-Upp. 366
Summaryp. 366
Problemsp. 367
Factorial Analysis of Variance: Fixed-Effects Modelp. 371
Two-Factor ANOVA Modelp. 372
Three-Factor and Higher-Order ANOVAp. 390
Factorial ANOVA With Unequal n'sp. 393
SPSS and G*Powerp. 395
Template and APA-Style Write-Upp. 417
Summaryp. 419
Problemsp. 420
Introduction to Analysis of Covariance: One-Factor Fixed-Effects Model With Single Covariatep. 427
Characteristics of the Modelp. 428
Layout of Datap. 431
ANCOVA Modelp. 431
ANCOVA Summary Tablep. 432
Partitioning the Sums of Squaresp. 433
Adjusted Means and Related Proceduresp. 434
Assumptions and Violation of Assumptionsp. 436
Examplep. 441
ANCOVA Without Randomizationp. 443
More Complex ANCOVA Modelsp. 444
Nonparametric ANCOVA Proceduresp. 444
SPSS and G*Powerp. 445
Template and APA-Style Paragraphp. 469
Summaryp. 471
Problemsp. 471
Random- and Mixed-Effects Analysis of Variance Modelsp. 477
One-Factor Random-Effects Modelp. 478
Two-Factor Random-Effects Modelp. 483
Two-Factor Mixed-Effects Modelp. 488
One-Factor Repeated Measures Designp. 493
Two-Factor Split-Plot or Mixed Designp. 500
SPSS and G*Powerp. 508
Template and APA-Style Write-Upp. 548
Summaryp. 551
Problemsp. 551
Hierarchical and Randomized Block Analysis of Variance Modelsp. 557
Two-Factor Hierarchical Modelp. 558
Two-Factor Randomized Block Design for n = 1p. 566
Two-Factor Randomized Block Design for n > 1p. 574
Friedman Testp. 574
Comparison of Various ANOVA Modelsp. 575
SPSSp. 576
Template and APA-Style Write-Upp. 603
Summaryp. 605
Problemsp. 605
Simple Linear Regressionp. 611
Concepts of Simple Linear Regressionp. 612
Population Simple Linear Regression Modelp. 614
Sample Simple Linear Regression Modelp. 615
SPSSp. 634
G*Powerp. 647
Template and APA-Style Write-Upp. 650
Summaryp. 652
Problemsp. 652
Multiple Regressionp. 657
Partial and Semipartial Correlationsp. 658
Multiple Linear Regressionp. 661
Methods of Entering Predictorsp. 676
Nonlinear Relationshipsp. 679
Interactionsp. 680
Categorical Predictorsp. 680
SPSSp. 682
G*Powerp. 698
Template and APA-Style Write-Upp. 701
Summaryp. 703
Problemsp. 704
Logistic Regressionp. 709
How Logistic Regression Worksp. 710
Logistic Regression Equationp. 711
Estimation and Model Fitp. 715
Significance Testsp. 716
Assumptions and Conditionsp. 721
Effect Sizep. 725
Methods of Predictor Entryp. 726
SPSSp. 727
G*Powerp. 746
Template and APA-Style Write-Upp. 749
What Is Next?p. 751
Summaryp. 752
Problemsp. 752
Appendix: Tablesp. 783
Referencesp. 783
Odd-Numbered Answers to Problemsp. 793
Author Indexp. 809
Subject Indexp. 813
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