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. The class is taught at a master's of biostatistics introductory level and requires Mathematical Biostatistics Boot Camp 1 as a prerequisite.
Developed in collaboration with Johns Hopkins Open Education Lab.
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.