Prerequisite: a grade of C or better in Theory of Probability (MATH-UA 233) or equivalent. Not open to students who have taken Probability and Statistics (MATH-UA 235). Introduction to the mathematical foundations and techniques of modern statistical analysis used in the interpretation of data in quantitative sciences. Mathematical theory of sampling; normal populations and distributions; chi-square, t, and F distributions; hypothesis testing; estimation; confidence intervals; sequential analysis; correlation, regression, and analysis of variance. Applications to the sciences.

Math (Undergraduate)

4 credits – 15 Weeks

#### Sections (Spring 2022)

**MATH-UA 234-000 (8382)**

01/24/2022 – 05/09/2022 Tue,Thu

12:00 AM – 1:00 PM (Early afternoon)

at Washington Square

Instructed by Nitzschner, Maximilian

**MATH-UA 234-000 (8383)**

01/24/2022 – 05/09/2022 Fri

2:00 PM – 3:00 PM (Early afternoon)

at Washington Square

Instructed by Plotkin, Ted

**MATH-UA 234-000 (9440)**

01/24/2022 – 05/09/2022 Tue,Thu

3:00 PM – 4:00 PM (Late afternoon)

at Washington Square

Instructed by Dies, Erik

**MATH-UA 234-000 (9441)**

01/24/2022 – 05/09/2022 Fri

3:00 PM – 4:00 PM (Late afternoon)

at Washington Square

Instructed by Plotkin, Ted