An Introduction to Statistical Concepts 4th edition by Debbie Hahs Vaughn, Richard Lomax – Ebook PDF Instant Download/Delivery: 1138650558, 9781138650558
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ISBN 10: 1138650558
ISBN 13: 9781138650558
Author: Debbie Hahs Vaughn, Richard Lomax
The new edition of An Introduction to Statistical Concepts is designed to help students really understand statistical concepts, the situations in which they can be used, and how to apply them to data. Hahs-Vaughn and Lomax discuss the most popular, along with many of the lesser-known, procedures and models, whilst also exploring nonparametric procedures used when standard assumptions are violated. They provide in-depth coverage of testing assumptions and highlight several online tools for computing statistics (e.g., effect sizes and their confidence intervals and power). This comprehensive, flexible, and accessible text includes a new chapter on mediation and moderation; expanded coverage of effect sizes; and discussions of sensitivity, specificity, false positive, and false negative, along with using the receiver operator characteristic (ROC) curve. In addition to instructions and screen shots for using SPSS, new to this edition is annotated script for using R. This book, noted for its crystal-clear explanations, and its inclusion of only the most crucial equations, is an invaluable resource for students undertaking a course in statistics in any number of social science and behavioral disciplines—from education, business, communication, exercise science, psychology, sociology and more.
An Introduction to Statistical Concepts 4th Table of contents:
1. Introduction
1.1 What Is the Value of Statistics?
1.2 Brief Introduction to the History of Statistics
1.3 General Statistical Definitions
1.4 Types of Variables
1.5 Scales of Measurement
1.6 Additional Resources
Problems
2. Data Representation
2.1 Tabular Display of Distributions
2.2 Graphical Display of Distributions
2.3 Percentiles
2.4 Recommendations Based on Measurement Scale
2.5 Computing Tables, Graphs, and More Using SPSS
2.6 Computing Tables, Graphs, and More Using R
2.7 Research Question Template and Example Write-Up
2.8 Additional Resources
Problems
3. Univariate Population Parameters and Sample Statistics
3.1 Summation Notation
3.2 Measures of Central Tendency
3.3 Measures of Dispersion
3.4 Computing Sample Statistics Using SPSS
3.5 Computing Sample Statistics Using R
3.6 Research Question Template and Example Write-Up
3.7 Additional Resources
Problems
4. The Normal Distribution and Standard Scores
4.1 The Normal Distribution and How It Works
4.2 Standard Scores and How They Work
4.3 Skewness and Kurtosis Statistics
4.4 Computing Graphs and Standard Scores Using SPSS
4.5 Computing Graphs and Standard Scores Using R
4.6 Research Question Template and Example Write-Up
4.7 Additional Resources
Problems
5. Introduction to Probability and Sample Statistics
5.1 Brief Introduction to Probability
5.2 Sampling and Estimation
5.3 Additional Resources
Problems
6. Introduction to Hypothesis Testing: Inferences About a Single Mean
6.1 Inferences About a Single Mean and How They Work
6.2 Computing Inferences About a Single Mean Using SPSS
6.3 Computing Inferences About a Single Mean Using R
6.4 Data Screening
6.5 Power Using G*Power
6.6 Research Question Template and Example Write-Up
6.7 Additional Resources
Problems
7. Inferences About the Difference Between Two Means
7.1 Inferences About Two Independent Means and How They Work
7.2 Inferences About Two Dependent Means and How They Work
7.3 Computing Inferences About Two Independent Means Using SPSS
7.4 Computing Inferences About Two Dependent Means Using SPSS
7.5 Computing Inferences About Two Independent Means Using R
7.6 Computing Inferences About Two Dependent Means Using R
7.7 Data Screening
7.8 G*Power
7.9 Research Question Template and Example Write-Up
7.10 Additional Resources
Problems
8. Inferences About Proportions
8.1 Inferences About Proportions Involving the Normal Distribution and How They Work
8.2 Inferences About Proportions Involving the Chi-Square Distribution and How They Work
8.3 Computing Inferences About Proportions Involving the Chi-Square Distribution Using SPSS
8.4 Computing Inferences About Proportions Involving the Chi-Square Distribution Using R
8.5 Data Screening
8.6 Power Using G*Power
8.7 Recommendations
8.8 Research Question Template and Example Write-Up
8.9 Additional Resources
Problems
9. Inferences About Variances
9.1 Inferences About Variances and How They Work
9.2 Assumptions
9.3 Sample Size, Power, and Effect Size
9.4 Computing Inferences About Variances Using SPSS
9.5 Computing Inferences About Variances Using R
9.6 Research Question Template and Example Write-Up
9.7 Additional Resources
Problems
10. Bivariate Measures of Association
10.1 What Bivariate Measures of Association Are and How They Work
10.2 Computing Bivariate Measures of Association Using SPSS
10.3 Computing Bivariate Measures of Association Using R
10.4 Data Screening
10.5 Power Using G*Power
10.6 Research Question Template and Example Write-Up
10.7 Additional Resources
Problems
11. One-Factor Analysis of Variance—Fixed-Effects Model
11.1 What One-Factor ANOVA Is and How It Works
11.2 Computing Parametric and Nonparametric Models Using SPSS
11.3 Computing Parametric and Nonparametric Models Using R
11.4 Data Screening
11.5 Power Using G*Power
11.6 Research Question Template and Example Write-Up
11.7 Additional Resources
Problems
12. Multiple Comparison Procedures
12.1 What Multiple Comparison Procedures Are and How They Work
12.2 Computing Multiple Comparison Procedures Using SPSS
12.3 Computing Multiple Comparison Procedures Using R
12.4 Research Question Template and Example Write-Up
Problems
13. Factorial Analysis of Variance—Fixed-Effects Model
13.1 What Two-Factor ANOVA Is and How It Works
13.2 What Three-Factor and Higher-Order ANOVA Models Are and How They Work
13.3 What the Factorial ANOVA with Unequal n’s Is and How It Works
13.4 Computing Factorial ANOVA Using SPSS
13.5 Computing Factorial ANOVA Using R
13.6 Data Screening
13.7 Power Using G*Power
13.8 Research Question Template and Example Write-Up
13.9 Additional Resources
Problems
14. Introduction to Analysis of Covariance: The One-Factor Fixed-Effects Model with a Single Covariate
14.1 What ANCOVA Is and How It Works
14.2 Computing ANCOVA Using SPSS
14.3 Computing ANCOVA Using R
14.4 Data Screening
14.5 Power Using G*Power
14.6 Research Question Template and Example Write-Up
14.7 Additional Resources
Problems
15. Random- and Mixed-Effects Analysis of Variance Models
15.1 The One-Factor Random-Effects Model
15.2 The Two-Factor Random-Effects Model
15.3 The two-Factor Mixed-Effects Model
15.4 The one-Factor Repeated Measures Design
15.5 The Two-Factor Split-Plot or Mixed Design
15.6 Computing ANOVA Models Using SPSS
15.7 Computing ANOVA Models Using R
15.8 Data Screening for the Two-Factor Split-Plot ANOVA
15.9 Power Using G*Power
15.10 Research Question Template and Example Write-Up
15.11 Additional Resources
Problems
16. Hierarchical and Randomized Block Analysis of Variance Models
16.1 What Hierarchical and Randomized Block ANOVA Models Are and How They Work
16.2 Mathematical Introduction Snapshot
16.3 Computing Hierarchical and Randomized Block ANOVA Models Using SPSS
16.4 Computing Hierarchical and Randomized Block Analysis of Variance Models Using R
16.5 Data Screening
16.6 Power Using G*Power
16.7 Research Question Template and Example Write-Up
16.8 Additional Resources
Problems
17. Simple Linear Regression
17.1 What Simple Linear Regression Is and How It Works
17.2 Mathematical Introduction Snapshot
17.3 Computing Simple Linear Regression Using SPSS
17.4 Computing Simple Linear Regression Using R
17.5 Data Screening
17.6 Power Using G*Power
17.7 Research Question Template and Example Write-Up
17.8 Additional Resources
Problems
18. Multiple Linear Regression
18.1 What Multiple Linear Regression Is and How It Works
18.2 Mathematical Introduction Snapshot
18.3 Computing Multiple Linear Regression Using SPSS
18.4 Computing Multiple Linear Regression Using R
18.5 Data Screening
18.6 Power Using G*Power
18.7 Research Question Template and Example Write-Up
18.8 Additional Resources
Problems
19. Logistic Regression
19.1 What Logistic Regression Is and How It Works
19.2 Mathematical Introduction Snapshot
19.3 Computing Logistic Regression Using SPSS
19.4 Computing Logistic Regression Using R
19.5 Data Screening
19.6 Power Using G*Power
19.7 Research Question Template and Example Write-Up
19.8 Additional Resources
Problems
20. Mediation and Moderation
20.1 What Mediation Is and How It Works
20.2 What Moderation Is and How It Works
20.3 Computing Mediation and Moderation Using SPSS
20.4 Computing Mediation and Moderation Using R
20.5 Additional Resources
Problems
Appendix: Tables
References
Name Index
Subject Index
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