Introduction
What will you learn?
- What is statistical thinking?
- How data is organized, described, and how inferences are made about data
- What are the different statistical tests out there? When can they be used? How do you interpret them?
- How to critically evaluate statistics
- How to be a wise consumer of psychological information, by understanding statistics, to make better decisions for your health and well-being!
Many careers use statistics! Although you are likely taking this course as your degree path requires it, you will find this class is important for you to be a good consumer of statistics and data literacy. This book takes on a more traditional approach to teaching statistics laying the foundation with computational formulas for descriptive and inferential statistics.
Quick overview of the 3 units in this textbook
Unit 1: The first unit in this course will introduce you to the principles of statistics and why we study and use them in the behavioral sciences. It covers the basic terminology and notation used for statistics, as well as how behavioral sciences think about, use, interpret, and communicate information and data. The unit concludes with a brief introduction to concepts in probability and sampling that underlie how scientists perform data analysis. The material in this unit serves as the building blocks for the logic and application of hypothesis testing, which is introduced in unit 2 and comprises the rest of the material in the course. Unit 1 reviews material in 8 chapters.
Unit 2: In unit 1, we learned the basics of statistics – what they are, how they work, and the mathematical and conceptual principles that guide them. In this unit, we will learn to use everything from the previous unit to test hypotheses, formal statements of research questions that form the backbone of statistical inference and scientific progress. This unit focuses on hypothesis tests about means, and unit 3 will continue to use hypothesis testing for other types of data, statistics, and relations. Unit 2 covers chapters 9 to 15.
Unit 3: The last unit in this course introduces you to analyzing data beyond having the predictor (independent) variable as categorical (nominal) with a continuous (interval/ratio) dependent variable. In this final unit we continue to use the same hypothesis testing logic and procedures on new types of data. We start with hypotheses using only continuous data and then look at a different kind of test statistic: a non-parametric statistic for only categorical data. With the basics of statistics covered in the textbook, the last chapter focuses on considerations for doing reproducible research.
Book adoption: If you are using this book, please let Alisa know! Dr. Alisa Beyer, alisa.beyer@cgc.edu
Attribution:
The contents of this work have been adapted from the following Open Access Resources:
Poldrack, Russell A. (2021). Statistical Thinking for the 21st Century, Available at: https://open.umn.edu/opentextbooks/textbooks/statistical-thinking-for-the-21st-century
Foster, Garett C.; Lane, David; Scott, David; Hebl, Mikki; Guerra, Rudy; Osherson, Dan; and Zimmer, Heidi, "An Introduction to Psychological Statistics" (2018). Open Educational Resources Collection. 4. Available at: https://irl.umsl.edu/oer/4
Online Statistics Education: A Multimedia Course of Study (http://onlinestatbook.com/). Project Leader: David M. Lane, Rice University.
Some of the text in the chapter also came from readings written by Lisa Degiorgio Worthy, Glendale Community College (AZ).
Changes to the previous works to tailor the text to fit the needs of the introductory statistics course for Maricopa County Community College students. Materials from the original sources have been combined, reorganized, and added to by the current author, and any conceptual, mathematical, or typographical errors are the responsibility of the current author.
