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Course Criteria
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4.00 Credits
Prerequisites: STA 215 An introduction to problems and techniques inherent to the design and analysis of experiments. There are broad applications across numerous disciplines in the sciences and the humanities. Topics include: analysis of variance, blocking, general factorial models, nested designs, confounding and fractional replication. A statistical software package will be used throughout the course (SAS, SPSS or MINITAB).
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4.00 Credits
Prerequisites: STA 215 This course introduces students to the use of sampling theory, the design and analysis of sample surveys, and robust statistical tests that are applicable in a wide range of real-world applications. Topics include: stratified sampling, cluster sampling, quota sampling, questionnaire design, and k-sample tests for paired and unpaired data.
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4.00 Credits
Prerequisites: STA 215 Regression concepts and techniques as a synthesis of theory, methods and applications. Topics include: multiple regression, interactions, partial and multiple correlation, polynomial regression and logistic regression and time series analysis. The SAS statistical software package will be used throughout the course.
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4.00 Credits
Prerequisites: STA 215 An introduction to a variety of multivariate statistical methods as aids to analyzing and interpreting large data sets. These methods will have general applications across a wide range of client disciplines. Topics include: principal components analysis, cluster analysis, discriminant analysis, multi-dimensional scaling and correspondence analysis. A statistical software package will be used throughout the course (SAS, SPSS or MINITAB).
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4.00 Credits
Prerequisites: (1) STA215; (2) CRI215 or CSC220 (or above); and (3) MAT 316 or one 300- level STA course. An introduction to data mining and predictive modeling. Topics include decision trees, link functions, logic regression, neural networks, TreeNet, support vector machine, text mining, association rules (market basket analysis), and link analysis.
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4.00 Credits
Prerequisites: STA 215 Course description: An introduction to the theory and application of statistical quality control. Topics include variables control charts ( X , R, and s), attributes control charts (p, np, c, and u), and non-Shewhart type charts (CUSUM, MA, and EWMA); rational subgrouping, Average Run Length, and O-C curves.
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4.00 Credits
Prerequisite: MAT 316 An introduction to that portion of Operations Research which deals with probabilistic techniques. Topics include: forecasting, queuing models, inventory control and simulation. Students will become conversant with a number of operations research software packages.
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4.00 Credits
Special topics in statistics that will vary by semester.
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1.00 - 8.00 Credits
(every semester) Prerequisite: By invitation only Student will study and/or do research independently in an appropriate area. A department member will be assigned to advise and direct the student.
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1.00 - 8.00 Credits
Prerequisite: Department permission. For individual pursuit of advanced topics within or beyond a student's major field of study which transcend the regularly available curriculum.
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