Statistical methods for understanding and interpreting biological and public health data.
Descriptive Statistics, Screening tests, ROC curves, prevalence and incidence of disease.
Application of regression to biological and health data sets: graphical data summary,statistical comparison of interventions by hypothesis tests and confidence intervals, correlation,and regression. Case studies.
Design and Analysis techniques for Epidemiologic Studies: Study designs, confounding and standardization, Meta analysis, Analysis of variance and covariance. crossover designs, clustered data, intraclass correlation, longitudinal analysis, missing data, case studies
Categorical health data: Contingency tables, Goodness of fit tests, Tests for binomial proportions, estimation of power and sample size, logistic regression, case studies
Person time health data: Inference for incidence rate data, power and sample size considerations, testing for trend, survival analysis, proportional hazard model, case studies
Case studies of health big data: techniques to summarize and display big data, descriptive and inferential methodologies
Clinical trials: statistical design and analysis aspects of clinical trials
Rosner, B. Fundamentals of biostatistics. Belmont, CA: Thomson-Brooks/Cole, 2006.
Wayne W. Daniel, Chad L. Cross, Biostatistics: A Foundation for Analysis in the Health Sciences (11thed.), John Wiley, NewYork, 2018.
S.C. Chow and J.P. Liu, Design and Analysis of Clinical Trials - Concepts & Methodologies (3rd Edition),John Wiley & Sons, NY, 2013.
Kutner, M., Nachtsheim, C., Neter, J. and Li, W. Applied Linear Statistical Models, 5th Edition,McGraw-Hill Companies, Boston, 2005.
Name(s) of other Academic units to whom the course may be relevant