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A Practical Extension of Introductory Statistics in Psychology using R
This book aims to provide a practical extension of introductory statistics typically taught in psychology into the general linear model (GLM) using R.
Ekarin E. Pongpipat, Ph.D., Giuseppe G. Miranda, Ph.D., Matthew J. Kmiecik, Ph.D.
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Front Matter
Abstract
Note on This PreTeXt Edition
1
Introduction
1.1
What exactly is the GLM?
1.2
How will this book be covered?
1.3
What won’t this book cover?
1.4
Why R?
1.5
Issues and Recommendations
1.6
License
2
Prerequisites
2.1
Knowledge
2.2
Software
3
R Packages
3.1
What are packages?
3.2
Packages
3.3
Install R Packages
3.4
Load R Packages
4
Datasets
4.1
Salaries Dataset
4.1.1
Data Wrangling
4.1.2
Descriptive Statistics
4.1.2.1
Categorical Variables
4.1.2.2
Continuous Variables
4.2
Anorexia Dataset
4.2.1
Data Wrangling
4.2.2
Descriptive Statistics
4.2.2.1
Categorical Variables
4.2.2.2
Continuous Variables
4.3
Use Your Own Dataset
5
Simple Linear Regression
5.1
Null and Research Hypotheses
5.2
Statistical Analyses
5.2.1
How Do We Read the ANOVA Source Table?
5.2.2
How Do We Read the Coefficients Table?
5.3
Statistical Decision
5.4
APA Statement
5.5
Visualization
6
Correlation
6.1
Null and Research Hypotheses
6.1.1
Traditional Approach
6.1.2
GLM Approach
6.2
Statistical Analysis
6.2.1
Traditional Approach
6.2.2
GLM Approach
6.3
Statistical Decision
6.4
APA Statement
6.5
Visualization
7
One Sample
t
-Test
7.1
Null and Research Hypotheses
7.1.1
Traditional Approach
7.1.2
GLM Approach
7.2
Statistical Analysis
7.2.1
Traditional Approach
7.2.2
GLM Approach
7.3
Statistical Decision
7.4
APA Statement
7.5
Visualization
8
Dependent Samples
t
-Test
8.1
Null and Research Hypotheses
8.1.1
Traditional Approach
8.1.2
GLM Approach
8.2
Statistical Analysis
8.2.1
Traditional Approach
8.2.2
GLM Approach
8.3
Statistical Decision
8.4
APA Statement
8.5
Visualization
9
Independent Samples
t
-Test
9.1
Null and Research Hypotheses
9.1.1
Traditional Approach
9.1.2
GLM Approach
9.2
Statistical Analysis
9.2.1
Traditional Approach
9.2.2
GLM Approach
9.3
Statistical Decision
9.4
APA Statement
9.5
Visualization
10
One-Way ANOVA
10.1
Coding Categorical Variables
10.1.1
Dummy Coding
10.1.2
Orthogonal Coding
10.2
Null and Research Hypotheses
10.2.1
Traditional Approach
10.2.2
GLM Approach
10.3
Statistical Analysis
10.3.1
Traditional Approach
10.3.2
GLM Approach
10.4
Statistical Decision
10.5
APA Statement
10.6
Visualization
10.6.1
Traditional
10.6.2
Orthogonal Contrast Coding
11
Factorial ANOVA
11.1
Null and Research Hypotheses
11.1.1
Traditional Approach
11.1.2
GLM Approach
11.2
Statistical Analysis
11.2.1
Traditional Approach
11.2.2
GLM Approach
11.3
Statistical Decision
11.4
APA Statement
11.5
Visualization
12
GLM Approach Summary
Back Matter
A
Acknowledgements
B
Authors
B.1
Ekarin E. Pongpipat, Ph.D.
B.2
Giuseppe G. Miranda, Ph.D.
B.3
Matthew J. Kmiecik, Ph.D.
References
A Practical Extension of Introductory Statistics in Psychology using R
This book aims to provide a practical extension of introductory statistics typically taught in psychology into the general linear model (GLM) using R.
Ekarin E. Pongpipat, Ph.D.
The University of Texas at Dallas
Giuseppe G. Miranda, Ph.D.
The University of Texas at Dallas
Matthew J. Kmiecik, Ph.D.
NorthShore University HealthSystem
May 21, 2026
Abstract
Note on This PreTeXt Edition
🔗
