HONS 217 Honors Statistics (3)

Honors Statistics introduces students to the world of stochastic phenomena and modeling including probability, statistical inference, and stochastic processes. The course covers the axioms of probability and fundamental laws of probability including the Law of Large Numbers, the Central Limit Theorem, conditioning, and Bayes Theorem. Using probability theory the course develops statistical inference procedures including point estimation, confidence intervals, hypothesis tests, and multiple linear regression. Elementary stochastic processes are covered via discrete-time Markov chains with applications. Real world examples and real data will be used to demonstrate the power and utility of stochastic modeling and statistical inference across a wide variety of disciplines. This is the Honors course version of MATH 250. Students may not receive credit for both.
Prerequisite(s): Honors College student, MATH 105 with a C- or better or MATH 111 or MATH 120 or permission of the instructor.
Course Frequency: Fall and Spring