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DSST 189
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Introduction to Statistical Modeling
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Topics will include exploratory data analysis, correlation, linear and multiple regression, design of experiments, basic probability, the normal distribution, sampling distributions, estimation, hypothesis testing and randomization approach to infere...
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DSST 289
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Introduction to Data Science
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Multiple linear regression, logistic regression, ANOVA and other modeling based topics. Exploratory graphical methods, model selection and model checking techniques will be emphasized with extensive use a statistical programming language (R) for data...
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DSST 329
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Probability
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Introduction to the theory, methods, and applications of randomness and random processes. Probability concepts, independence, random variables, expectation, discrete and continuous probability distributions, moment-generating functions, simulation, j...
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DSST 330
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Mathematical Statistics
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Introduction to basic principles and procedures for statistical estimation and model fitting. Parameter estimation, likelihood methods, unbiasedness, sufficiency, confidence regions, Bayesian inference, significance testing, likelihood ratio tests, l...
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DSST 389
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Advanced Data Science
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Computational statistics and statistical algorithms for building predictive models from large data sets. Topics include model complexity, hyper-parameter tuning, over- and under-fitting, and the evaluation of predictive performance. Models covered in...
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DSST 390
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Directed Independent Study
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Topics independently pursued under supervision of faculty member.
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DSST 395
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Special Topics in Data Science & Statistics
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Selected topics in data science and statistics.
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