Statistical Concepts - A Second Course

✍ Scribed by Debbie L. Hahs-Vaughn, Richard G. Lomax

• Publisher: Routledge
• Year: 2020
• Tongue: English
• Leaves: 783
• Edition: 5
• Category: Library

✦ Synopsis

Statistical Concepts―A Second Course presents the last 10 chapters from An Introduction to Statistical Concepts, Fourth Edition. Designed for second and upper-level statistics courses, this book highlights how statistics work and how best to utilize them to aid students in the analysis of their own data and the interpretation of research results.

In this new edition, Hahs-Vaughn and Lomax discuss sensitivity, specificity, false positive and false negative errors. Coverage of effect sizes has been expanded upon and more organizational features (to summarize key concepts) have been included. A final chapter on mediation and moderation has been added for a more complete presentation of regression models. In addition to instructions and screen shots for using SPSS, new to this edition is annotated script for using R.

This book acts as a clear and accessible instructional tool to help readers fully understand statistical concepts and how to apply them to data. It is an invaluable resource for students undertaking a course in statistics in any number of social science and behavioral science disciplines.

✦ Table of Contents

Cover
Half Title
Title
Copyright
Dedication
Contents
Preface
Acknowledgments
1. One-Factor Analysis of Variance—Fixed-Effects Model
1.1 What One-Factor Analysis of Variance Is and How It Works
1.2 Computing Parametric and Nonparametric Models Using SPSS
1.3 Computing Parametric and Nonparametric Models Using R
1.4 Data Screening
1.5 Power Using GPower
1.6 Research Question Template and Example Write-Up
1.7 Additional Resources
Problems
2. Multiple Comparison Procedures
2.1 What Multiple Comparison Procedures Are and How They Work
2.2 Computing Multiple Comparison Procedures Using SPSS
2.3 Computing Multiple Comparison Procedures Using R
2.4 Research Question Template and Example Write-Up
Problems
3. Factorial Analysis of Variance—Fixed-Effects Model
3.1 What Two-Factor ANOVA Is and How It Works
3.2 What Three-Factor and Higher-Order ANOVA Models Are and How They Work
3.3 What the Factorial ANOVA With Unequal n’s Is and How It Works
3.4 Computing Factorial ANOVA Using SPSS
3.5 Computing Factorial ANOVA Using R
3.6 Data Screening
3.7 Power Using GPower
3.8 Research Question Template and Example Write-Up
3.9 Additional Resources
Problems
4. Introduction to Analysis of Covariance: The One-Factor Fixed-Effects Model With a Single Covariate
4.1 What ANCOVA Is and How It Works
4.2 Computing ANCOVA Using SPSS
4.3 Computing ANCOVA Using R
4.4 Data Screening
4.5 Power Using GPower
4.6 Research Question Template and Example Write-Up
4.7 Additional Resources
Problems
5. Random- and Mixed-Effects Analysis of Variance Models
5.1 The One-Factor Random-Effects Model
5.2 The Two-Factor Random-Effects Model
5.3 The Two-Factor Mixed-Effects Model
5.4 The One-Factor Repeated Measures Design
5.5 The Two-Factor Split‑Plot or Mixed Design
5.6 Computing ANOVA Models Using SPSS
5.7 Computing ANOVA Models Using R
5.8 Data Screening for the Two-Factor Split-Plot ANOVA
5.9 Power Using GPower
5.10 Research Question Template and Example Write-Up
5.11 Additional Resources
Problems
6. Hierarchical and Randomized Block Analysis of Variance Models
6.1 What Hierarchical and Randomized Block Analysis of Variance Models Are and How They Work
6.2 Mathematical Introduction Snapshot
6.3 Computing Hierarchical and Randomized Block ANOVA Models Using SPSS
6.4 Computing Hierarchical and Randomized Block Analysis of Variance Models Using R
6.5 Data Screening
6.6 Power Using GPower
6.7 Research Question Template and Example Write-Up
6.8 Additional Resources
Problems
7. Simple Linear Regression
7.1 What Simple Linear Regression Is and How It Works
7.2 Mathematical Introduction Snapshot
7.3 Computing Simple Linear Regression Using SPSS
7.4 Computing Simple Linear Regression Using R
7.5 Data Screening
7.6 Power Using GPower
7.7 Research Question Template and Example Write-Up
7.8 Additional Resources
Problems
8. Multiple Linear Regression
8.1 What Multiple Linear Regression is and How It Works
8.2 Mathematical Introduction Snapshot
8.3 Computing Multiple Linear Regression Using SPSS
8.4 Computing Multiple Linear Regression Using R
8.5 Data Screening
8.6 Power Using GPower
8.7 Research Question Template and Example Write-Up
8.8 Additional Resources
Problems
9. Logistic Regression
9.1 What Logistic Regression Is and How It Works
9.2 Mathematical Introduction Snapshot
9.3 Computing Logistic Regression Using SPSS
9.4 Computing Logistic Regression Using R
9.5 Data Screening
9.6 Power Using GPower
9.7 Research Question Template and Example Write-Up
9.8 Additional Resources
Problems
10. Mediation and Moderation
10.1 What Mediation and Moderation Is and How It Works
10.2 What Moderation Is and How It Works
10.3 Computing Mediation and Moderation Using SPSS
10.4 Computing Mediation and Moderation Using R
10.5 Additional Resources
Problems
Appendix: Tables
References
Name Index
Subject Index