MATH 242 - Applied Statistical Modeling

Semester Offered: Fall or Spring
1 unit(s)

Applied Statistical Modeling is offered as a second course in statistics in which we present a set of case studies and introduce appropriate statistical modeling techniques for each. Topics may include: multiple linear regression, logistic regression, log-linear regression, survival analysis, an introduction to Bayesian modeling, and modeling via simulation. Other topics may be substituted for these or added as time allows. Students are expected to conduct data analyses in R.

Prerequisite(s): MATH 126 and MATH 127 (or the equivalent); and AP credit in statistics, MATH 141 or MATH 240.

Course Format: CLS