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Statistical Concepts : A Second Course,9780415880077
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Statistical Concepts : A Second Course

by ;
Edition:
4th
ISBN13:

9780415880077

ISBN10:
0415880076
Format:
Nonspecific Binding
Pub. Date:
3/12/2012
Publisher(s):
Routledge/Psych

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What version or edition is this?
This is the 4th edition with a publication date of 3/12/2012.
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Summary

Statistical Concepts consists of the last 9 chapters of An Introduction to Statistical Concepts, 3rded. Designed for the second coursein statistics it is one of the few texts that focuses just on intermediate statistics. The flexible coverage allows instructors to 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 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 allnew 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 Boxesprovide 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 in the book. The first six chapters cover the basic and advanced analysis of variance models. The next three examine linear, multiple, and logistic regression models, topics that are often neglected in other texts. Intended for courses in intermediate statistics and/or statistics II taught in education and/or the behavioral sciences, predominantly at the master's or doctoral level. A rudimentary knowledge of algebra and introductory statistics is assumed.

Table of Contents

Prefacep. xi
Acknowledgmentsp. xv
One-Factor Analysis of Variance: Fixed-Effects Modelp. 1
Characteristics of One-Factor ANOVA Modelp. 2
Layout of Datap. 6
ANOVA Theoryp. 6
ANOVA Modelp. 12
Assumptions and Violation of Assumptionsp. 19
Unequal n's or Unbalanced Procedurep. 22
Alternative ANOVA Proceduresp. 22
SPSS and G*Powerp. 23
Template and APA-Style Write-Upp. 44
Summaryp. 46
Problemsp. 46
Multiple Comparison Proceduresp. 51
Concepts of Multiple Comparison Proceduresp. 52
Selected Multiple Comparison Proceduresp. 58
SPSSp. 72
Template and APA-Style Write-Upp. 76
Summaryp. 76
Problemsp. 77
Factorial Analysis of Variance: Fixed-Effects Modelp. 81
Two-Factor ANOVA Modelp. 82
Three-Factor and Higher-Order ANOVAp. 100
Factorial ANOVA With Unequal n'sp. 103
SPSS and G*Powerp. 105
Template and APA-Style Write-Upp. 127
Summaryp. 129
Problemsp. 130
Introduction to Analysis of Covariance: One-Factor Fixed-Effects Model With Single Covariatep. 137
Characteristics of the Modelp. 138
Layout of Datap. 141
ANCOVA Modelp. 141
ANCOVA Summary Tablep. 142
Partitioning the Sums of Squaresp. 143
Adjusted Means and Related Proceduresp. 144
Assumptions and Violation of Assumptionsp. 146
Examplep. 151
ANCOVA Without Randomizationp. 153
More Complex ANCOVA Modelsp. 154
Nonparametric ANCOVA Proceduresp. 154
SPSS and G*Powerp. 155
Template and APA-Style Paragraphp. 179
Summaryp. 181
Problemsp. 181
Random- and Mixed-Effects Analysis of Variance Modelsp. 187
One-Factor Random-Effects Modelp. 188
Two-Factor Random-Effects Modelp. 193
Two-Factor Mixed-Effects Modelp. 198
One-Factor Repeated Measures Designp. 203
Two-Factor Split-Plot or Mixed Designp. 210
SPSS and G*Powerp. 218
Template and APA-Style Write-Upp. 258
Summaryp. 261
Problemsp. 261
Hierarchical and Randomized Block Analysis of Variance Modelsp. 267
Two-Factor Hierarchical Modelp. 268
Two-Factor Randomized Block Design for n = 1p. 276
Two-Factor Randomized Block Design for n > 1p. 284
Friedman Testp. 284
Comparison of Various ANOVA Modelsp. 285
SPSSp. 286
Template and APA-Style Write-Upp. 313
Summaryp. 315
Problemsp. 315
Simple Linear Regressionp. 321
Concepts of Simple Linear Regressionp. 322
Population Simple Linear Regression Modelp. 324
Sample Simple Linear Regression Modelp. 325
SPSSp. 344
G*Powerp. 357
Template and APA-Style Write-Upp. 360
Summaryp. 362
Problemsp. 362
Multiple Regressionp. 367
Partial and Semipartial Correlationsp. 368
Multiple Linear Regressionp. 371
Methods of Entering Predictorsp. 386
Nonlinear Relationshipsp. 389
Interactionsp. 390
Categorical Predictorsp. 390
SPSSp. 392
G*Powerp. 408
Template and APA-Style Write-Upp. 411
Summaryp. 413
Problemsp. 414
Logistic Regressionp. 419
How Logistic Regression Worksp. 420
Logistic Regression Equationp. 421
Estimation and Model Fitp. 425
Significance Testsp. 426
Assumptions and Conditionsp. 431
Effect Sizep. 435
Methods of Predictor Entryp. 436
SPSSp. 437
G*Powerp. 456
Template and APA-Style Write-Upp. 459
What Is Next?p. 461
Summaryp. 462
Problemsp. 462
Appendix: Tablesp. 467
Referencesp. 493
Odd-Numbered Answers to Problemsp. 501
Author Indexp. 507
Subject Indexp. 511
Table of Contents provided by Ingram. All Rights Reserved.


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