This course aims to provide an overview of the formulas and concepts of basic statistical analysis approaches used in the behavioral sciences. Furthermore, the practice exercises in this book will challenge and expose you to different ways of applying the concepts.
This resource intends to provide step-by-step instructions on how to perform statistical computations. In addition, it is to serve as a guide or a reference as the course progresses from simple calculations to more advanced statistical techniques. By the end of the course, I hope that readers will better understand the reasoning behind many statistical approaches and can ultimately match a simple research design to appropriate statistical analysis.
The received exposure to diverse styles of statistical analysis instruction and more than ten years of teaching at the undergraduate level inspired me to create this material. I hope this primer on statistical analysis will serve as a foundation for students to learn more advanced statistical analysis techniques used in scientific journals. For others, I hope that the material will help foster a greater appreciation for the rigor involved in conducting and drawing conclusions from empirical evidence.
Chapter 1: Variables and Scores
Chapter 2: Summarizing Scores
Chapter 3: Normal Population Distributions
Chapter 4: How Are Hypotheses Are Tested?
Chapter 5: Hypothesis Testing Issues to Consider
Chapter 6: Inferential Statistics: t-Test versus z-Test
Chapter 7: Dependent Means t-test
Chapter 8: Independent Means t-Test
Chapter 9: Analysis of Variance
Chapter 10: Factorial ANOVA
Chapter 11: Correlations