The course provides students with an understanding of basic concepts of data analysis and statistical inference in the medical and health sciences, with an emphasis on the application of statistical methods to the design and interpretation of biological experiments and comparative data. Specific topics include tools for describing central tendency and variability in data, methods for performing inference on population means and proportions via sample data, statistical hypothesis testing and its application to group comparisons, issues of power and sample size in study designs, and random sample and other study types.

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