Course List - Master of Applied Statistics

Required Courses (15 credits)
STAT 414	Introduction to Probability Theory Probability spaces, discrete and continuous random variables, transformations, expectations, generating functions, conditional distributions, law of large numbers, central limit theorems. Math prerequisites: Multidimensional calculus and knowledge of matrix algebra/linear algebra STAT prerequisites: STAT 500 and STAT 501 strongly encouraged	3 credits
STAT 415	Introduction to Mathematical Statistics A theoretical treatment of statistical inference, including sufficiency, estimation, testing, regression, analysis of variance, and chi-square tests. Prerequisites: STAT 414	3 credits
STAT 501	Regression Methods Analysis of research data through simple and multiple regression and correlation; polynomial models; indicator variables; step-wise, piece-wise, and logistic regression. Prerequisites: 6 credits of statistics or STAT 500 plus matrix algebra	3 credits
STAT 502	Analysis of Variance and Design of Experiments Analysis of variance and design concepts; factorial, nested, and unbalanced data; ANCOVA; blocked, Latin square, split-plot, repeated measures designs. Prerequisites: STAT 501	3 credits
STAT 580	Statistical Consulting Practicum I General principles of statistical consulting and statistical consulting experience. Preparation of reports, presentations, and communication aspects of consulting are discussed. Prerequisites: STAT 502, STAT 503 or STAT 504 or STAT 506	2 credits
STAT 581	Statistical Consulting Practicum II Statistical consulting experience including client meetings, development of recommendation reports, and discussion of consulting solutions. Prerequisites: STAT 580	1 credit

 

Elective Courses (15 credits)
STAT 464	Applied Nonparametric Statistics Tests based on nominal and ordinal data for both related and independent samples. Chi-square tests, correlation. Prerequisites: STAT 200, STAT 220, STAT 240, STAT 250, STAT 301 or STAT 401	3 credits
STAT 480	Introduction to SAS Introduction to SAS with emphasis on reading, manipulating and summarizing data. Prerequisites: 3 credits of statistics or STAT 500	1 credit
STAT 481	Intermediate SAS for Data Management Intermediate SAS for data management. Prerequisite: STAT 480	1 credit
STAT 482	Advanced Statistical Procedures in SAS This course covers advanced statistical procedures in SAS, including ANOVA, GIM, CORR, REG, MANOVA, FACTOR, DISCRIM, LOGISTIC, MIXED, GRAPH, EXPORT, and SQL. Prerequisites: STAT 480, STAT 481	1 credit
STAT 483	Statistical Analysis System Programming Introduction, intermediate, and advanced topics in SAS. Note: Credit cannot be received for both STAT 483 and STAT 480/481/482. Prerequisites: 3 credits in statistics	3 credits
STAT 497C	Topics in Stat Computing with R Topics include: I) Basic background on R II) Manipulating data I III) Finding help IV) Simple univariate data V) Importing data VI) Documenting your work VII) Manipulating data II VIII) Reptitive tasks — loops and the apply () family IX) Visual data X) Basic analyses (as much as possible you'll be working with real data).	1 credit
STAT 500	Applied Statistics Descriptive statistics, hypothesis testing, power, estimation, confidence intervals, regression, one- and 2-way ANOVA, Chi-square tests, diagnostics. Prerequisites: 3 credits of undergraduate course work in statistics	3 credits
STAT 503	Design of Experiments Design principles; optimality; confounding in split-plot, repeated measures, fractional factorial, response surface, and balanced/partially balanced incomplete block designs. Prerequisites: STAT 501, STAT 502	3 credits
STAT 504	Analysis of Discrete Data Models for frequency arrays; goodness-of-fit tests; two-, three-, and higher- way tables; latent and logistic models. Prerequisites: STAT 502 and matrix algebra	3 credits
STAT 505	Applied Multivariate Statistical Analysis Analysis of multivariate data; T2-tests; particle correlation; discrimination; MANOVA; cluster analysis; regression; growth curves; factor analysis; principal components; canonical correlations. Prerequisites: STAT 501, STAT 502	3 credits
STAT 506	Sampling Theory and Methods Theory and application of sampling from finite populations. Prerequisites: 3 credits of statistics or STAT 500	3 credits
STAT 507	Epidemiology Research Methods Research and quantitative methods for analysis of epidemiologic observational studies. Non-randomized, intervention studies for human health, and disease treatment. Prerequisites: STAT 250 or equivalent	3 credits
STAT 509	Clinical Trials An introduction to the design and statistical analysis of randomized and observational studies in biomedical research. Prerequisites: 3 credits of statistics or STAT 500	3 credits
STAT 510	Applied Time Series Analysis Identification of models for empirical data collected over time. Use of models in forecasting. Prerequisites: STAT 462, STAT 501, or STAT 511	3 credits
STAT 557	Data Mining I This course introduces data mining and statistical/machine learning, and their applications in information retrieval, database management, and image analysis.	3 credits