Measures of Correlation and Contingency

This course introduces analyses of correlation and contingency, providing students with a comprehensive understanding of these essential statistical concepts. Students learn to identify research questions that warrant use of these tools, gaining the ability to discern when they are appropriate methods for analyzing relationships between variables. Students learn to articulate the direction and strength of a correlation. 

Through practical examples and exercises, students become adept at interpreting correlation coefficients. Students then explore the theoretical underpinnings of correlation, gaining insight into why and how it measures the relationship between variables. This section of the course demystifies the mathematical foundations of correlation, making it accessible and understandable. The course also provides a thorough examination of how relationships between categorical variables can be explored using contingency tables. Students learn to recognize situations where contingency tables are the most suitable analytical tool. The course highlights the usefulness of contingency tables for describing and summarizing a possible relationship between two categorical variables. 

Throughout the course, a blend of theoretical knowledge and practical application ensures that students not only understand the concepts but also know how to apply them in real-world scenarios, and the use and demonstration of the jamovi statistical software program for examining correlational data and contingency tables provides students the tools they need to begin to explore these analyses on their own

Learning objectives

• Describe research questions that involve correlational logic.
• Explain how correlations vary in by kind and degree.
• Explain how the formula for the Pearson correlation coefficient captures dependencies between variables.
• Describe the research questions that lead to use of contingency tables.
• Identify relationships between variables in a contingency table.