Official Description: This is a core graduate course for the PhD program in
Epidemiology. This course will provide the theoretical basis for fundamental
elements that are commonly used in epidemiologic and other experimental studies,
and emphasize real applications and implications on practice so that the
learning materials would be well suited for applied scientists (i.e.,
non-statisticians). As heavy users of statistics and statistical methods and
software, it is highly ideal that epidemiologists understand what is going on
inside statistical software when they use it in daily life. This course will
also help students use specific methods correctly with proper understanding of
underlying theory and assumptions entailed. Specifically, this course will focus
on statistical estimation and inference, including regression, ANOVA and
hypothesis testing. If time permits, we will go over additional important topics
and widely adopted methods such as sample size and power calculation, resampling
and some recent developments and discussions in modern statistics.

Instructors: Alternates between Heejung Bang and and Ana-Maria

Other info and comments: Here is the syllabus from
(MS Word

Software used: Let us know in the comments

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