Course Description
Calculus-based introduction to probability and mathematical statistics for students in Biostatistics, Epidemiology and other fields requiring a technical understanding of statistical inference. Random variables, expectation, laws of large numbers and central limit theorem. Point estimation, confidence intervals, and hypothesis testing for statistical models with public health and biomedical applications.
Athena Title
INTERMED MATH STAT
Prerequisite
MATH 2410
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Course Objectives
A prime objective of this course is to present techniques and basic results of probability and mathematical statistics. Students will learn how to use specific statistical distributions and general modes of statistical thinking to make inferences from data, and to support an argument with quantitative information. Students will learn the mathematical and probabilistic underpinnings of statistical theory, which are essential for understanding and properly applying statistical techniques used in other fields such as epidemiology, health policy, education, and related disciplines.
Topical Outline
1. Introduction to probability; 2. Random variables; 3. Expectation; 4. Inequalities; 5. Laws of large numbers and central limit theorem; 6. Statistical models; 7. Point estimation using method of moments, least squares and maximum likelihood; 8. Confidence intervals; 9. Hypothesis testing.