Apr 19, 2024  
2018-2019 Graduate Catalog 
    
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2018-2019 Graduate Catalog [ARCHIVED CATALOG]

MATH 648 - Computational Statistics

4 Credit(s)

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.

Enrollment Requirements:
Prerequisite: MATH 647  or permission of instructor/

039233:1