Computational Statistics
Course #: MATH 448, Class #: 2588, Section #: 01
Description
This course is an introduction to the fundamental ideas and techniques of statistical inference. The course demonstrates how and when to use statistical methods, explains the mathematical background behind them and illustrates them with case studies. Topics covered include the Central Limit Theorem, parameter estimation, confidence intervals, hypothesis testing, type I and II errors, power, significance level, p-value, likelihood ration tests, t-test, paired and 2-population t-tests, goodness-of-fit tests, chi-square tests, contingency tables, exact tests, nonparametric tests, ANOVA and regression models. Statistical software such as R, Matlab, or Python, will be used to analyze real-world data.
Prerequisites
MATH 345 or permission of instructor
Course Details
Date / Time
1/25/27 - 5/12/27
TuTh 5:30p.m. – 6:45p.m.
Location
McCormack M01-0209
Credits
3
Session
Regular Academic Session
Class Dates
1/25/2027 - 5/12/2027
Location
McCormack M01-0209
Enrolled / Capacity
0 / 30
Status
Open
Instructor
To be Announced