Course Descriptions

E ST 503 - SAS Basics 2 cr. (1+2P) (formerly called 505C)A brief introduction to the statistical software package, SAS, and its utilization in an interactive computing environment, primarily CMS/SAS. Provides a fundamental understanding of the structure of SAS, its data management capabilities, and how to invoke a variety of descriptive and simple statistical SAS procedures. Statistical concepts will not be a primary focus. Corequisite: E ST 456, E ST 461, E ST 501, or E ST 505, or consent of instructor. (offered spring and fall)

E ST 504 - Statistical Software Appl. (1 cr.) (formerly called 506C)Optional computing course to accompany E ST 506. Computer analysis of topics covered in E ST 505 & 506. Prerequisite: E ST 503 or consent of the instructor. Co-requisite: E ST 506 or 502. (offered every spring and fall)

E ST 505 -Statistical Inference I 4 cr. (3+2P) Aqualitative introduction to the concepts and methods of statistical inference. Sampling, frequency distributions (z, t, x, F), estimation, and testing. One-way analysis of variance. Simple linear regression. Prerequisite: consent of the instructor.

E ST 506 - Statistical Inference II 3 cr. (2+2P) Introduction to multiple regression through partial and sequential sums of squares; the analysis of variance for balanced studies: multiple comparisons, contrasts, factorials, experimental designs through split plots. Prerequisite: E ST 505 or consent of the instructor. (offered every spring and fall)

E ST 507 - Advanced Regression (3 cr.) Examination of multiple regression; residual analysis, collinearity, variable selection, weighted least squares, polynomial models, and nonlinear regression: linearizable and intrinsically nonlinear models. Prerequisites: E ST 504 and one of 506 or 502, or consent of instructor. (offered every fall)

E ST 508 - Analysis of Adv. Designs (3 cr.) Complete and incomplete block designs; fixed, mixed and random models; unbalanced data; analysis of covariance; nested experiments; fractional factorials. Prerequisite: E ST 504 and one of 506 or 502, or consent of instructor. (offered spring of even years)

E ST 521 - Sampling Methodology 2 cr. (3+2P) Methodology of sampling finite populations using unrestricted, stratified, systematic, and multistage selections; regressions and ratio estimators. Material will be covered in weeks 1-8 of a 15-week semester. Prerequisite: E ST 456, E ST/STAT 465, or E ST 502, or E ST 505, or consent of instructor. (offered every fall)

E ST 523 - Biological Sampling (3 cr.) Methods of sampling biological populations: area frame, quadrat, line intercept, line transect, and capture-recapture, removal methods. Prerequisite: E ST 505, or consent of instructor. (offered every spring)

E ST 545 -Time Series Analysis and Applications (3 cr.) A systematic exposition of the methods for analyzing, modeling, and forecasting time series. Emphasizes underlying ideas and methods rather than detailed mathematical derivations, using SAS, BMDP, IMSL, and Fortan. Prerequisites: E ST 506, and E ST 504, or consent of instructor. (offered spring of odd years)

E ST 550 -Special Topics (1-4 cr.) Specific subjects to be announced in the Schedule of Classes. Maximum of 4 credits per semester. No more than 9 credits toward a degree.

E ST 555 - Applied Multivariate Analysis (3 cr.) Multivariate analysis of linear statistical models, including MANOVA and repeated measures. Analysis of correlation and covariance structures, including principal components, factor analysis, and canonical correlation. Classification and discrimination techniques. Prerequisites: E ST 506 and E ST 504 or consent of instructor. (offered every spring)