Statistics Courses

STA 216 Intermediate Applied Statistics

Project-oriented introduction to major statistical techniques using a statistical package such as SAS or SPSS. Hypothesis testing, {t-test}, multivariate regression, analysis of variance, analysis of covariance, chi-square tests, non-parametric statistics. Offered every semester. Prerequisite: STA 215 or STA 312. Credits: 3

STA 318 Statistical Computing

A detailed study of the advanced features of major statistical packages used in statistical computing, such as SAS and SPSS. Emphasis on the data entry, data manipulation, data storage, data simulation, and graphical display features of these packages. Offered on sufficient demand. Prerequisite: STA 215. Credits: 3

STA 321 Applied Regression Analysis

Multivariate regression analysis with emphasis on application using a statistical software package. Topics include method of least squares, residual analysis, co-linearity, data transformation, polynomial regression, general linear model, selecting a best regression model, and logistic regression. Offered fall semester on sufficient demand. Prerequisite: STA 216. Credits: 3

STA 416 Multivariate Data Analysis

Multivariate analysis with emphasis on application using a statistical package such as SAS or SPSS. Topics include principal components analysis, factor analysis, discriminant analysis, logistic regression, cluster analysis, multivariate analysis of variance, and canonical correlation analysis. Offered fall semester on sufficient demand. Prerequisite: STA 216. Credits: 3



Page last modified October 21, 2015