Course Requirements​

The certificate program requires successful completion of six courses in Applied Statistics.

Students in the Certificate in Applied Statistics program must apply for degree conferral via Campus Connection in advance of their final quarter in the program in order to have their coursework audited for the awarding of their certificate.


 

MAT 441

APPLIED STATISTICS I

Parametric and non-parametric statistical inferential methods for the univariate and bivariate situations using SAS. Specific topics include classical and exploratory graphical & numerical methods of data descriptions; inference about means, medians, and associations including analysis of variance and linear regression. Data analytic projects are an integral part of the course.

MAT 442

APPLIED STATISTICS II

A continuation of MAT 441. Repeated measures design, association, analysis of covariance, and multivariate relationships. Diagnostics and model building. Methods of categorical data analysis. Logistical regression and log-linear models. Data analytical projects using SAS are an integral part of the course.
Prerequisites:
MAT 441 is a prerequisite for this class.

MAT 443

APPLIED STATISTICS III

A continuation of MAT 442. The course material generalizes univariate methods of inference to multivariate situations using SAS. Specific topics include canonical correlation, discriminate analysis, principal component analysis, factor analysis, and multivariate analysis of variance. Emphasis in the curse is on data analytic projects.
Prerequisites:
MAT 442 is a prerequisite for this class.

MAT 456

APPLIED REGRESSION ANALYSIS

Simple linear, multiple, polynomial and general linear regression models. Model diagnostics; Model selection and Validation. Cross-listed with MAT 356.
Prerequisites:
MAT 453 is a prerequisite for this class.

MAT 457

NONPARAMETRIC STATISTICS

Inference concerning location and scale parameters, goodness of fit tests, association analysis and tests of randomness using distribution free procedures. Bootstrap techniques. Smoothing methodologies. Cross-listed with MAT 357.
Prerequisites:
MAT 453 is a prerequisite for this class.

MAT 528

DESIGN AND ANALYSIS OF EXPERIMENTS

Single-factor fixed, random and mixed designs with and without restrictions on randomizations, including randomized block designs, Latin & Graeco-Latin squares. Factorial and fractional factorial experiments. Nested and split-plot designs. Confounding and response surface methodology.
Prerequisites:
MAT 453 is a prerequisite for this class.

MAT 526

SAMPLING THEORY AND METHODS

Simple random, stratified, systematic and cluster sampling. Multistage and area sampling. Random-response and capture-release models. Cross-listed as MAT 326.
Prerequisites:
MAT 453 is a prerequisite for this class.

MAT 458

STATISTICAL QUALITY CONTROL

History; Deming guide to quality; graphical techniques of process control; Schewhart's control charts for means, ranges, standard deviations, individual measurements, and attributes; process capabilities and statistical tolerance; cumulative-sum charts. product liability; acceptance sampling; product and process design; applications and case studies.