MATH 141 - Introduction to Probability and Statistics

The basic ideas of probability including properties of expectation, the law of large numbers, and the central limit theorem are discussed. These ideas are applied to the problems of statistical inference, including estimation and hypothesis testing. The linear regression model is introduced, and the problems of statistical inference and model validation are studied in this context. A portion of the course is devoted to statistical computing and graphics.

Unit(s): 1
Group Distribution Requirement(s): Distribution Group III
Prerequisite(s): Three years of high school mathematics
Instructional Method: Lecture-conference
Grading Mode: Letter grading (A-F)
Group Distribution Learning Outcome(s):

Use and evaluate quantitative data or modeling, or use logical/mathematical reasoning to evaluate, test or prove statements.
Given a problem or question, formulate a hypothesis or conjecture, and design an experiment, collect data, or use mathematical reasoning to test or validate it.