Courses in Statistics

STA 2323. Statistical Methods. Topics include descriptive statistics, correlation, regression, introduction to probability, basic probability distributions, confidence intervals, hypothesis testing, 1-way analysis of variance. Prerequisites: MTH 1243 or MTH 1273.

STA 2611, 2612, 2613, 2614, 2615, 2616. Internship in Statistics. See MTH 4621.

STA 4013. Applied Regression Analysis. Simple linear regression and associated special topics, multiple linear regression, indicator variables, influence diagnostics, assumption analysis, selection of "best subset", nonstandard regression models, logistic regression, nonlinear regression models. Prerequisite: STA 2323 and departmental permission. 

STA 4023. Applied Analysis of Variance. One-way ANOVA, two-way additive ANOVA, two-way ANOVA with interaction, analysis of covariance, Levene’s Test for homogeneity, ad hoc procedures, Kruskal Wallis Test, Randomized F test, and an introduction to experimental design. Prerequisite: STA 2323 and departmental permission.

STA 4033. Nonparametric Statistical Methods. An introduction to distribution-free procedures which include the sign test, Wilcoxon tests, chi-squared tests, McNemar’s test, bootstrapping, and rank-based ANOVA. The efficiency of these is compared with the corresponding classical procedures. Prerequisite: STA 2323 and departmental permission. 

STA 3163. Probability and Statistics I. See MTH 3163.

STA 4043. Statistical Analysis of Time Series. Time series components, descriptive smoothing methods, regression models for time series data, forecasting via exponential smoothing, evaluation of forecasts, autocorrelation, ARIMA models and Box-Jenkins methods, combining forecasts, frequency domain analysis, filtering. Prerequisite: STA 3013 and departmental permission.

STA 4433. Probability and Statistics II. See MTH 4433.

STA 4621, 4622, 4623, 4624, 4625, 4626.  Internship in Statistics. See MTH 4621.