Computational Statistics
Course #: MATH 648
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 ratiotests, t-test, paired and 2-population t-test, goodness-of-fit 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.
Pre Requisites: Pre-requisite: MATH 647 or permission of instructor.
Offered in:
2025 Spring
| Section | Class Number | Schedule/Time | Instructor | Location | |
|---|---|---|---|---|---|
| 01 | 8220 | TuTh 5:30 - 6:45 pm |
TBD | Wheatley W01-0047 | |
|
Session:
Regular
Class Dates:
01/27/2025 - 05/14/2025
Capacity:
10
Enrolled:
0
Status:
Open
Credits:
4/4
Class Notes:
Pre Requisites:
Pre-requisite: MATH 647 or permission of instructor.
Course Attributes:
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