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Course Criteria
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0.00 Credits
Credit Hours: 0.00. Cooperative Work Experience. Typically offered Fall Spring Summer. 0.000 Credit Hours Levels: Graduate, Professional, Undergraduate Schedule Types: Experiential College of Science College Statistics Department Course Attributes: Coop, Full-Time Privileges, Upper Division
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1.00 - 5.00 Credits
Credit Hours: 1.00 to 5.00. Supervised reading course or special topics course at the junior level for undergraduates are given under this number. Permission of instructor required. Typically offered Summer Fall Spring. 1.000 TO 5.000 Credit Hours Levels: Graduate, Professional, Undergraduate Schedule Types: Distance Learning, Individual Study, Lecture College of Science College Statistics Department Course Attributes: Upper Division, Variable Title
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3.00 Credits
Credit Hours: 3.00. (MA 416) An introduction to mathematical probability suitable as preparation for actuarial science, statistical theory, and mathematical modeling. General probability rules, conditional probability and Bayes theorem, discrete and continuous random variables, moments and moment generating functions, joint and conditional distributions, standard discrete and continuous distributions and their properties, law of large numbers and central limit theorem. Credit cannot be given for more than one of STAT 225, 311, or 416. Prerequisite: multivariate calculus. Typically offered Fall Spring. 3.000 Credit Hours Levels: Graduate, Professional, Undergraduate Schedule Types: Distance Learning, Lecture College of Science College Statistics Department Course Attributes: Upper Division
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3.00 Credits
Credit Hours: 3.00. An introduction to the mathematical theory of statistical inference, emphasizing inference for standard parametric families of distributions. Properties of estimators. Bayes and maximum likelihood estimation. Sufficient statistics. Properties of test of hypotheses. Most powerful and likelihood-ratio tests. Distribution theory for common statistics based on normal distributions. Typically offered Fall Spring. 3.000 Credit Hours Levels: Graduate, Professional, Undergraduate Schedule Types: Distance Learning, Lecture College of Science College Statistics Department Course Attributes: Upper Division
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3.00 Credits
Credit Hours: 3.00. An introduction to time series analysis suitable for actuarial science, engineering, and sciences. Model building and forecasting with ARMA and ARIMA models. Resampling methods for confidence intervals. Multivariate, state-space, and nonlinear models. Volatility models (ARCH and GARCH). Smoothing in time series. Typically offered Summer Fall Spring. 3.000 Credit Hours Levels: Graduate, Professional, Undergraduate Schedule Types: Distance Learning, Lecture College of Science College Statistics Department Course Attributes: Upper Division
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3.00 Credits
Credit Hours: 3.00. A variety of different statistical methods are applied to data sets in a number of different fields. Statistical methods covered include applied regression analysis, experimental design, sampling, time series, categorical data analysis and applied multivariate analysis. This course provides a summary of how statistical ideas are useful in understanding and designing research in many areas of study. Each student investigates and reports on six case study projects. Statistical computer programs are used. Typically offered Fall Spring. 3.000 Credit Hours Levels: Graduate, Professional, Undergraduate Schedule Types: Distance Learning, Lecture Regional Campus Only College Course Attributes: Upper Division
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3.00 Credits
Credit Hours: 3.00. Mathematical foundations of actuarial science, emphasizing probability models for life contingencies as the basis for analyzing life insurance and life annuities and determining premiums. This course, together with its sequel, STAT 473, provides the background for Course 3 of the Society of Actuaries and the Casualty Actuarial Society. Typically offered Fall. 3.000 Credit Hours Levels: Graduate, Professional, Undergraduate Schedule Types: Distance Learning, Lecture College of Science College Statistics Department Course Attributes: Upper Division
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3.00 Credits
Credit Hours: 3.00. Continuation of STAT 472. Together, these courses cover contingent payment models, survival models, frequency and severity models, compound distribution models, stochastic process models, and ruin models. Typically offered Spring. 3.000 Credit Hours Levels: Graduate, Professional, Undergraduate Schedule Types: Distance Learning, Lecture College of Science College Statistics Department Course Attributes: Upper Division
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3.00 Credits
Credit Hours: 3.00. (C S 478 and BIOL 478) Bioinformatics is broadly defined as the study of molecular biological information, targeting particularly the enormous volume of DNA sequence and functional complexity embedded in entire genomes. Topics will include understanding the evolutionary organization of genes (genomics), the structure and function of gene products (proteomics), and the dynamics of gene expression in biological processes (transcriptomics). Inherently, bioinformatics is interdisciplinary, melding various applications of computational science with biology. This jointly taught course introduces analytical methods from biology, statistics and computer science that are necessary for bioinformatics investigations. The course is intended for junior and senior undergraduates from various science backgrounds. Our objective is to develop the skills of both tool users and tool designers in this important new field of research. . Typically offered Fall. 3.000 Credit Hours Levels: Graduate, Professional, Undergraduate Schedule Types: Distance Learning, Lecture College of Science College Statistics Department Course Attributes: Upper Division
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3.00 Credits
Credit Hours: 3.00. This material provides an introduction to modeling and covers important actuarial methods that are useful in modeling. Students will be introduced to survival, severity, frequency and aggregate models, and use statistical methods to estimate parameters of such models given sample data. The student will further learn to identify steps in the modeling process, understand the underlying assumptions implicit in each family of models, recognize which assumptions are applicable in a given business application, and appropriately adjust the models for impact of insurance coverage modifications. The student will be introduced to a variety of tools for the calibration and evaluation of the models. Permission of instructor required. Typically offered Fall Spring Summer. 3.000 Credit Hours Levels: Graduate, Professional, Undergraduate Schedule Types: Distance Learning, Lecture College of Science College Statistics Department Course Attributes: Upper Division
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