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Statistical Concepts A Second Course

ISBN-10: 0415880076
ISBN-13: 9780415880077
Edition: 4th 2012 (Revised)
List price: $50.99
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Description: 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  More...

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Book details

List price: $50.99
Edition: 4th
Copyright year: 2012
Publisher: Taylor & Francis Group
Publication date: 4/4/2012
Binding: Paperback
Pages: 532
Size: 6.75" wide x 9.75" long x 1.00" tall
Weight: 2.332
Language: English

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.

Richard G. Lomax is a Professor in the School of Educational Policy and Leadership at The Ohio State University. He received his Ph.D. in Educational Research Methodology from the University of Pittsburgh. His research focuses on models of literacy acquisition, multivariate statistics, and assessment. He has twice served as a Fulbright Scholar and is a Fellow of the American Educational Research Association.Debbie L. Hahs-Vaughn is an Associate Professor in the College of Education at the University of Central Florida. She received her Ph.D. in Educational Research from the University of Alabama. Her research focuses on methodological and substantive research using complex survey data, program evaluation, and practitioner use of research to inform their practice. Dr. Hahs-Vaughn was the recipient of the 2007 College of Education Excellence in Graduate Teaching Award, 2009 College of Education Distinguished Researcher Award, 2009 Teaching Incentive Program Award, and 2009 Research Incentive Award. She is currently the Executive Editor of the Measurement, Statistics, and Research Design section of the Journal of Experimental Education.

Preface
Acknowledgments
One-Factor Analysis of Variance: Fixed-Effects Model
Characteristics of One-Factor ANOVA Model
Layout of Data
ANOVA Theory
ANOVA Model
Assumptions and Violation of Assumptions
Unequal n's or Unbalanced Procedure
Alternative ANOVA Procedures
SPSS and G*Power
Template and APA-Style Write-Up
Summary
Problems
Multiple Comparison Procedures
Concepts of Multiple Comparison Procedures
Selected Multiple Comparison Procedures
SPSS
Template and APA-Style Write-Up
Summary
Problems
Factorial Analysis of Variance: Fixed-Effects Model
Two-Factor ANOVA Model
Three-Factor and Higher-Order ANOVA
Factorial ANOVA With Unequal n's
SPSS and G*Power
Template and APA-Style Write-Up
Summary
Problems
Introduction to Analysis of Covariance: One-Factor Fixed-Effects Model With Single Covariate
Characteristics of the Model
Layout of Data
ANCOVA Model
ANCOVA Summary Table
Partitioning the Sums of Squares
Adjusted Means and Related Procedures
Assumptions and Violation of Assumptions
Example
ANCOVA Without Randomization
More Complex ANCOVA Models
Nonparametric ANCOVA Procedures
SPSS and G*Power
Template and APA-Style Paragraph
Summary
Problems
Random- and Mixed-Effects Analysis of Variance Models
One-Factor Random-Effects Model
Two-Factor Random-Effects Model
Two-Factor Mixed-Effects Model
One-Factor Repeated Measures Design
Two-Factor Split-Plot or Mixed Design
SPSS and G*Power
Template and APA-Style Write-Up
Summary
Problems
Hierarchical and Randomized Block Analysis of Variance Models
Two-Factor Hierarchical Model
Two-Factor Randomized Block Design for n = 1
Two-Factor Randomized Block Design for n > 1
Friedman Test
Comparison of Various ANOVA Models
SPSS
Template and APA-Style Write-Up
Summary
Problems
Simple Linear Regression
Concepts of Simple Linear Regression
Population Simple Linear Regression Model
Sample Simple Linear Regression Model
SPSS
G*Power
Template and APA-Style Write-Up
Summary
Problems
Multiple Regression
Partial and Semipartial Correlations
Multiple Linear Regression
Methods of Entering Predictors
Nonlinear Relationships
Interactions
Categorical Predictors
SPSS
G*Power
Template and APA-Style Write-Up
Summary
Problems
Logistic Regression
How Logistic Regression Works
Logistic Regression Equation
Estimation and Model Fit
Significance Tests
Assumptions and Conditions
Effect Size
Methods of Predictor Entry
SPSS
G*Power
Template and APA-Style Write-Up
What Is Next?
Summary
Problems
Appendix: Tables
References
Odd-Numbered Answers to Problems
Author Index
Subject Index

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