Introduction to Statistical Concepts Third Edition

Name: Introduction to Statistical Concepts Third Edition
Price: 16.83 USD
Availability: InStock
ISBN: 9780415880053

ISBN-10: 041588005X

ISBN-13: 9780415880053

Edition: 3rd 2012 (Revised)

Authors: Richard G. Lomax, Debbie L. Hahs-Vaughn

List price: $95.00

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Description:

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.

Book details

List price: $95.00
Edition: 3rd
Copyright year: 2012
Publisher: Taylor & Francis Group
Publication date: 4/4/2012
Binding: Hardcover
Pages: 840
Size: 7.25" wide x 10.25" long x 1.75" tall
Weight: 4.576
Language: English

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,…



Preface


Acknowledgments



Introduction



What Is the Value of Statistics?



Brief Introduction to History of Statistics



General Statistical Definitions



Types of Variables



Scales of Measurement



Summary


Problems



Data Representation



Tabular Display of Distributions



Graphical Display of Distributions



Percentiles



SPSS



Templates for Research Questions and APA-Style Paragraph



Summary


Problems



Univariate Population Parameters and Sample Statistics



Summation Notation



Measures of Central Tendency



Measures of Dispersion



SPSS



Templates for Research Questions and APA-Style Paragraph



Summary


Problems



Normal Distribution and Standard Scores



Normal Distribution



Standard Scores



Skewness and Kurtosis Statistics



SPSS



Templates for Research Questions and APA-Style Paragraph



Summary


Problems



Introduction to Probability and Sample Statistics



Brief Introduction to Probability



Sampling and Estimation



Summary


Appendix: Probability That at Least Two Individuals Have the Same Birthday


Problems



Introduction to Hypothesis Testing: Inferences About a Single Mean



Types of Hypotheses



Types of Decision Errors



Level of Significance (ï¿½)



Overview of Steps in Decision-Making Process



Inferences About ï¿½ When ï¿½ Is Known



Type II Error (ï¿½) and Power (1-ï¿½)



Statistical Versus Practical Significance



Inferences About ï¿½ When ï¿½ Is Unknown



SPSS



G*Power



Template and APA-Style Write-Up



Summary


Problems



Inferences About the Difference Between Two Means



New Concepts



Inferences About Two Independent Means



Inferences About Two Dependent Means



SPSS



G&Power



Template and APA-Style Write-Up



Summary


Problems



Inferences About Proportions



Inferences About Proportions Involving Normal Distribution



Inferences About Proportions Involving Chi-Square Distribution



SPSS



G*Power



Template and APA-Style Write-Up



Summary


Problems



Inferences About Variances



New Concepts



Inferences About Single Variance



Inferences About Two Dependent Variances



Inferences About Two or More Independent Variances (Homogeneity of Variance Tests)



SPSS



Template and APA-Style Write-Up



Summary


Problems



Bivariate Measures of Association



Scatterplot



Covariance



Pearson Product-Moment Correlation Coefficient



Inferences About Pearson Product-Moment Correlation Coefficient



Assumptions and Issues Regarding Correlations



Other Measures of Association



SPSS



G*Power



Template and APA-Style Write-Up



Summary


Problems



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