Overview

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This is primarily aimed at first- and second-year undergraduates interested in psychology, data analysis, and quantitative research methods along with high school students and professionals with similar interests. This course provides a comprehensive understanding of chi-square analyses of contingency tables, including when and how to use them, formulating appropriate hypotheses, and understanding their underlying logic and assumptions. Students will gain practical skills in conducting chi-square goodness-of-fit tests and tests of independence, as well as analyzing effect sizes. Table of Contents: The Frequency Tables and Chi-Square Test The Chi-Square Goodness-of-Fit Test The Chi-Square Test of Independence

Syllabus

Learn With PsycLearn Essentials

This module introduces you to your PsycLearn Essentials course. Find out what’s included in this course and how to navigate the modules and lessons. You’ll also learn valuable study tips for successful learning.

PsycLearn Essentials APA Student Resources

This module provides a variety of information and tools from the American Psychological Association (APA) that will help inspire you as you complete your coursework and plan your career goals. Get discounted access to Academic Writer, APA’s online tool for writing effectively, as well as valuable advice that will help you develop and strengthen your skillset for learning success and future employment. Additionally, explore resources on various psychological issues. This module also includes APA resources on scholarly research and writing; a list of sites providing valuable resources on diversity, equity, and inclusion in psychology education and in the professional community; resources on a career in psychology; and links to career opportunities at the APA. You can also view videos that offer tips on dealing with stress.

Frequency Tables and the Chi-Square Test

This course will explain when to use a chi-square test and review the two types of chi-square tests that are used for frequency data: the goodness-of-fit test and the test of independence, including when each is appropriate for use as a null hypothesis significance test. The logic of the chi-square statistic will be covered, including the relevant statistical assumptions. The steps to conducting each chi-square test will be explained and activities will present scenarios where each chi-square test can be calculated, including the steps to conducting the test with statistical software. Finally, you will learn about how to interpret effect sizes for chi-square analyses.