APPLIED REGRESSION ANALYSIS

STAT 333

Course Description

An introduction to regression with emphasis on the practical aspects. Topics include: straight-line model, role of assumptions, residual analysis, transformations, multiple regression (with some use of matrix notation), multicollinearity, subset selection, and a brief introduction to mixed models.

Prerequisties

(STAT 240 , STAT 301 , 302, STAT 312 , STAT 324 , STAT 371 , ECON 310 , BME 325 , or ISYE 210 ) and (STAT 327 or STAT 303 , or concurrent enrollment)

Satisfies

STAT 456 , ACTSCI 640 , ACTSCI 652 , STAT 351 , ECON 695 , STAT 575 , STAT 443 , ACTSCI 655 , STAT 411 , BMI/STAT 620 , COMPSCI/STAT 471 , ECON 570 , STAT 421 , ACTSCI 654 , ACTSCI 657 , FINANCE 325 , ECON/FINANCE 320 , ACTSCI 650 , ME 536 , COMPSCI 541 , STAT 433 , ACTSCI 300 , STAT 461 , FINANCE 330 , GENBUS 656 , and STAT 349

Credits

Offered

Fall, Spring, Summer

Grade Point Average

3.36

1.15% from Historical

Completion Rate

100%

4.07% from Historical

A Rate

32.56%

-28.35% from Historical

Class Size

-14.53% from Historical

Instructors (2025 Fall)

Sorted by ratings from Rate My Professors

STAT 324

Descriptive statistics, probability concepts and distributions, random variables. Hypothesis tests and confidence intervals for one- and two-sample problems. Linear regression, model checking, and inference. Analysis of variance and basic ideas in experimental design. Utilizes the R programming language.

THEORY AND APPLICATION OF REGRESSION AND ANALYSIS OF VARIANCE II

STAT 850

Theory and applications of the general linear model; graphical methods; simultaneous inference; regression diagnostics; analysis of variance of fixed, random and mixed effects models; ANCOVA: violations of assumptions.

THEORY AND APPLICATION OF REGRESSION AND ANALYSIS OF VARIANCE I

STAT 849

REGRESSION MODELS IN EDUCATION

EDPSYCH 763

An applied introduction to regression techniques is given, covering nonparametric regression, multiple linear regression and logistic regression. All applied analyses are done in the statistical programming language R.

APPLIED ECONOMETRIC ANALYSIS I

AAE 636

Introduction to the standard linear regression model with an emphasis on application issues. Includes statistical foundation, hypothesis testing, functional form, model selection and procedures for handling violations of model assumption.

APPLIED REGRESSION ANALYSIS

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