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Course Criteria
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3.00 Credits
Stochastic processes and statistical inference including: Type I and Type II errors, MLE, Neyman-Pearson lemma, order statistics, Poisson processes, ANOVA, nonparametric tests, comparing models and Bayesian parameter estimation.
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3.00 Credits
The field of statistical learning encompasses the theory and data analytic techniques developed to process and make sense of evolving data challenges arising in the fields of data science and machine learning. This course will cover the theoretical underpinnings of supervised and unsupervised learning techniques, including generalized linear models, classification, dimension reduction, and cluster analysis. R and R-studio will be used for illustrative purposes. A working knowledge of linear algebra and multivariate calculus is assumed. Previous experience suing R software package is also assumed.
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3.00 Credits
An introduction to creating, solving, analyzing and interpreting real-world time-series and forecasting models. Topics include linear, autoregressive, moving average and other forecasting and time-series techniques, transfer functions, multivariate model building, stationary and nonstationary techniques. Applications may include all areas where forecasting is required including transportation, finance, scheduling, networks, and supply chains. Appropriate software tools for analyzing forecasting models including software such as SAS and spreadsheet software will be taught.
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3.00 Credits
A comprehensive coverage of modern quality control techniques including the design of statistical process control systems, acceptance sampling and process improvement.
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1.00 - 3.00 Credits
A unique and specifically focused course within the general purview of a department which intends to offer it on a "one time only" basis and not as a permanent part of the department's curriculum.
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1.00 - 6.00 Credits
A workshop is a program which is usually of short duration, narrow in scope, often non-traditional in content and format, and on a timely topic.
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1.00 - 3.00 Credits
A Selected Topics course is a normal, departmental offering which is directly related to the discipline, but because of its specialized nature, may not be able to be offered on a yearly basis by the department.
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1.00 - 3.00 Credits
Independent Study courses give students the opportunity to pursue research and/or studies that are not part of the university's traditional course offerings. Students work one on one or in small groups with faculty guidance and are typically required to submit a final paper or project as determined by the supervising professor.
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1.00 Credits
In this seminar, we will explore the history of statistics and the field of statistics today. Students will learn about current topics of interest in the field technical, ethical, and societal--and will research a current technical topic of interest. This is a capstone course for statistics students.
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1.00 - 6.00 Credits
A workshop is a program which is usually of short duration, narrow in scope, often non-traditional in content and format, and on a timely topic.
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