This course examines the theory behind statistical inference. Students will review probability theory, sampling distributions, methods of estimation, and hypothesis testing. Students will learn more advanced inferential techniques such as maximum likelihood estimation, bootstrapping, Bayesian methods, likelihood ratio testing, and confidence intervals. There will be an emphasis on the theory of these approaches in addition to their application. Prerequisite: STAT 2000 with a minimum grade of C and MATH 3020 with a minimum grade of C or instructor permission.
This course examines the theory behind statistical inference. Students will review probability theory, sampling distributions, methods of estimation, and hypothesis testing. Students will learn more advanced inferential techniques such as maximum likelihood estimation, bootstrapping, Bayesian methods, likelihood ratio testing, and confidence intervals. There will be an emphasis on the theory of these approaches in addition to their application. Prerequisite: STAT 2000 with a minimum grade of C and MATH 3020 with a minimum grade of C or instructor permission.
