Public health and healthcare delivery is constantly inundated with data from sources, including clinical trials, observational and longitudinal studies, genomics, and more. Having a firm grasp of the statistical computing skill-set can help you analyze this information effectively, and translate the flow of data into meaningful information that can inform decisions to improve the health of populations.
Epidemiology research can produce a lot of data— how that data is analyzed can be the key to creating impactful health interventions.
Get a comprehensive introduction to the use of biostatistics in the field of public health, while learning to compute and interpret descriptive and inferential statistics using SAS JMP®.
This program introduces students to statistical computing with focus on the SAS package. Emphasis is on manipulating data sets and basic statistical procedures such as t-tests, chi-square tests, and correlation.
Meta-Analysis is the gold standard statistical approach to combine the results of multiple studies and to examine sources of heterogeneity and potential biases.
Systematic reviews (SR) are increasingly used to inform clinical and public health practice. SR seek to collate all evidence that fits pre-specified eligibility criteria in order to address a specific research question.