Essentials of Statistics for the Behavioral Sciences

Get introduced to the how and why of statistical practice in the behavioral sciences as Essentials of Statistics for the Behavioral Sciences uses storytelling and real-world examples to reinforce the material for you to comprehend easier.

Susan A. Nolan is Professor of Psychology at Seton Hall University in New Jersey. A graduate of the College of the Holy Cross, she earned her Ph.D. in psychology from Northwestern University. Susan researches interpersonal consequences of mental illness and the role of gender in science and technology fields. Her research has been funded by the National Science Foundation. Susan served as a nongovernmental representative  from the American Psychological Association (APA) to the United Nations for five years, and is Vice President for Diversity and International Relations of the Society for the Teaching of Psychology. She is the 2014–2015 President of the Eastern Psychological Association (EPA), and is a Fellow of both EPA and APA. Tom Heinzen is Professor of Psychology at William Paterson University of New Jersey. A graduate of Rockford College, he earned his Ph.D. in social psychology at the State University of New York at Albany. After publishing his first book on frustration  and creativity in government, Heinzen worked as a public policy research associate, consulted for the Johns Hopkins Center for Talented Youth, and then began his teaching career. He founded William Paterson University’s Psychology Club, established an undergraduate research conference, and has been awarded various teaching honors while continuing to write articles, books, and plays that support the teaching of general psychology and statistics. Heinzen, a fellow of the Eastern Psychological Association, is also the editor of Many Things to Tell You, a volume of poetry by elderly writers. His current  research involves applying game design to higher education.

1. An Introduction to Statistics and Research Design

2. Frequency Distributions

3. Visual Displays of Data

4. Central Tendency and Variability

5. Sampling and Probability

6. The Normal Curve, Standardization, and z Scores

7. Hypothesis Testing with z Tests

8. Confidence Intervals, Effect Size, and Statistical Power

9. The Single-Sample t Test and The Paired-Samples t Test

10. The Independent-Samples t Test

11. One-Way ANOVA

12. Two-Way Between-Groups ANOVA

13. Correlation

14. Regression

15. Nonparametric Tests

Appendices

A. Reference for Basic Mathematics

B. Statistical Tables

C. Solutions to Odd-Numbered End-of-Chapter Problems

D. Solutions to Check Your Learning Problems

E. Choosing the Appropriate Statistical Test

F. Reporting Statistics

G. Building Better Graphs Using Excel