ENROLL

Laura Chihara

Introduction to statistics and data analysis. Practical aspects of statistics, including extensive use of statistical software, interpretation and communication of results, will be emphasized. Topics include: exploratory data analysis, correlation and linear regression, design of experiments, basic probability, the normal distribution, randomization approach to inference, sampling distributions, estimation, hypothesis testing, and two-way tables. Students who have received credit for Mathematics 115 may petition the department to seek approval to register for Mathematics 215. Students who have taken Mathematics 211 are encouraged to consider the more advanced Mathematics 265-275 Probability-Statistics sequence.

Prerequisite: Not open to students who have already received credit for Math 115, Psychology 200/201, Sociology/Anthropology 239 or Math 275.

Sophomore Priority

Waitlist for Juniors and Seniors: MATH 215.WL1 (Synonym 48856)

Laura Chihara

Many data sets violate a central assumption underlying modeling via multiple regression, namely that the observations be independent. For example, longitudinal studies of test scores of children at different ages, analysis of birthweights of pups from the same litters, and electrical activity on different parts of the brain measured on a sample of patients all involve observations that are correlated. In this course, we will earn methods to address this problem; we will also learn about general linear models of which logistic and Poisson regression are special cases.

Prerequisite: Math 245 and Math 275 or permission of instructor. Familiarity with matrix algebra helpful but not required