MATH 5112 - Mathematical Statistics for Data Analytics

3 credit hours
Students will study a variety of aspects of statistical estimation, beginning with principles of maximum likelihood estimation and confidence intervals, and then examining properties of statistical estimators such as sufficiency and consistency. Bayesian estimation will be discussed, and contrasted with traditional estimation in terms of both theory and practical use. Hypothesis testing will be examined for the principle of likelihood ratios - examples will focus on inferences about means, variances, proportions, and differences in means and proportions, while emphasizing the ability to generalize these tools to novel problems as well.

Prerequisite Course: MATH 5111 or MATH 3411 or MATH 5310
Terms Typically Offered: Summer