17_Chi Square Tests

Statistics Made Simple

In this episode of the podcast, we delve into the world of statistics with a detailed discussion on “Chi Square Tests”. Our conversation begins by exploring how categorical variables like happiness can be quantitatively analyzed through statistical methods. We discuss the concept of ordered categorical variables, using happiness as a case study to illustrate how responses ranging from "very happy" to "not too happy" can be treated quantitatively.

We then transition into the practical application of Chi Square Tests, explaining the process of picking and analyzing variables in research. Key points include understanding variable coding, interpreting negative correlations, and the importance of correct variable usage for accurate research conclusions.

The episode further breaks down the Chi Square Test itself, starting with the basics of hypothesis testing for categorical variables that have multiple categories. Through engaging examples like the game of rock-paper-scissors, we illustrate how to calculate expected counts, test statistics, and p-values, and discuss the significance of these values in research.

Listeners will gain insight into the complexities of statistical tests, including how to handle multiple categories and the steps involved in computing chi-square statistics. Whether you're a student grappling with statistical concepts or a professional looking to refine your data analysis skills, this episode provides a thorough understanding of Chi Square Tests and their application in real-world scenarios.

*****

Textbook: ⁠⁠Statistics: Unlocking the Power of Data⁠⁠

Students can use the Promotion Code "LOCK5" for a 10% discount.

Instructors can request a free Digital Evaluation Copy.

Lecture slides and additional course material can be obtained by emailing [e-mail]

--- Support this podcast: https://podcasters.spotify.com/pod/show/statistics/support