MATH 324. Statistics.
Credits: 3
Offered by: Mathematics and Statistics (Faculty of Science)
Terms offered: Fall 2026, Winter 2027
View offerings for Fall 2026 or Winter 2027 in Visual Schedule Builder.
Description
Sampling distributions, including Normal, Chi-squared, Student’s t, and F distributions.
Sampling properties of the sample mean and variance. Point estimation: bias, variance, mean squared error, consistency, sufficiency, UMVUE. Method of moments and maximum likelihood estimation. One- and two-sample inference. Confidence intervals and sample size determination. Hypothesis testing, Type 1 and Type 2 errors, power, and p-values. The Neyman Pearson framework and likelihood ratio tests.
Linear models used as illustrative examples, linking them to topics in estimation and
hypothesis testing. One-way analysis of variance (ANOVA) and contingency tables.
- Fall and Winter
- Prerequisite: MATH 323 or equivalent
- Restriction: Not open to students who have taken or are taking MATH 357
- You may not be able to receive credit for this course and other statistic courses. Be sure to check the Course Overlap section under Faculty Degree Requirements in the Arts or Science section of the Calendar.