Correlations and t-tests

Correlations and t-tests builds on the foundational statistical skills you learned in Introduction to Statistical Concepts and Describing Data to help you explore relationships and compare group outcomes in healthcare data. In this course, you’ll start by learning how to measure the strength and direction of relationships between variables using correlation techniques. You will then learn how to use independent sample t-tests and ANOVA to quantify differences between groups. With real-world healthcare examples and hands-on practice in R, you’ll gain practical experience analyzing data and interpreting results to inform evidence-based decisions. Topics include correlation interpretation, assumptions of t-tests and ANOVA, statistical significance, and the appropriate use of each method in clinical and research settings. This course is ideal for learners pursuing careers in nursing, public health, clinical research, or allied health who want to strengthen their ability to analyze and interpret healthcare data with confidence. 3b:T

• Explain the concept of correlation and interpret the strength and direction of relationships between two healthcare-related variables.
• Differentiate between independent and paired samples t-tests and identify when to use each in healthcare research.
• Conduct and interpret t-tests and ANOVA using R, including assumptions, test statistics, and p-values, to compare means across groups.

• STATS-411: Introduction to Statistical Concepts and Describing Data