Johns Hopkins Bloomberg School of Public Health gives online course on Mathematical Biostatistics Boot Camp 2, which is a part of the "Data Science" Specialization. This course deals with learning the fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples.
About the course
This class presents fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples. Students having taken this class should be able to summarize samples, perform relevant hypothesis tests and perform a collection of two sample comparisons. Classical non-parametric methods and discrete data analysis methods are discussed.
- Hypothesis Testing
- Power and sample size and two group tests
- Tests for binomial proportions
- Two sample binomial tests, delta method
- Fisher's exact tests, Chi-squared tests
- Simpson's paradox, confounding
- Retrospective case-control studies, exact inference for the odds ratio
- Methods for matched pairs, McNemar's, conditional versus marginal odds ratios
- Non-parametric tests, permutation tests
- Inference for Poisson counts
Students should take Mathematical Biostatistics Boot Camp 1 before enrolling in this course. Knowledge of calculus, set theory and a high level of mathematical literacy are prerequisites for this class.
This course consists of video lectures, weekly homework assignments, discussion forums, and weekly quizzes.
August 4, 2014 - September 22, 2014
For further information, click here.