Upon completion of this course, students are expected to:
1. Recognize and give examples of different types of data arising in public health and clinical studies;
2. Interpret differences in data distributions via visual displays;
3. Calculate standard normal scores and resulting probabilities;
4. Calculate and interpret confidence intervals for population means and proportions;
5. Interpret and explain a p-value;
6. Perform a two-sample t-test, interpret the results, and calculate a 95% confidence interval for the difference in population means;
7. Select an appropriate test for comparing two populations on a continuous measure;
8. Understand and interpret results from Analysis of Variance (ANOVA);
9. Choose an appropriate method for comparing proportions between two groups, and construct a 95% confidence interval for the difference in population proportions;
10. Understand and interpret relative risks and odds ratios when comparing two populations;
11. Describe different types of studies;
12. Understand confounding and interaction in studies;
13. Understand high-throughput genotyping and its data analysis;
14. Understand precision medicine, digital medicine, continuous physiological dynamics and their analysis.