Introduction to Statistical Concepts

ISBN-10: 041588005X

ISBN-13: 9780415880053

Edition: 3rd 2012 (Revised)

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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.

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Book details

List price: $80.00
Edition: 3rd
Copyright year: 2012
Publisher: Taylor & Francis Group
Publication date: 3/1/2012
Binding: Hardcover
Pages: 840
Size: 7.25" wide x 10.25" long x 1.75" tall
Weight: 4.048
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, 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
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 (�)
Overview of Steps in Decision-Making Process
Inferences About � When � Is Known
Type II Error (�) and Power (1-�)
Statistical Versus Practical Significance
Inferences About � When � 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
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