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Course Criteria
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3.00 Credits
Fall. Prerequisite: MATH 117 or MATH 118 or MATH 124 or MATH 125 or MATH 126 or MATH 141 or MATH 155 or MATH 160. Credit allowed for only one of the following: ERHS 307/STAT 307, STAT 301, STAT 311, or STAT 315. Classification, descriptive statistics; inference, testing, estimation; categorical data analysis; odds ratio.
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3.00 Credits
Spring. Prerequisite: STAT 311. One-way analysis of variance, factorial designs, blocked designs, multiple comparisons of means, and multiple regression.
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3.00 Credits
Fall, Spring, Summer. Prerequisite: MATH 161 or MATH 255. Credit allowed for only one course: STAT 301, STAT 307/ERHS 307, STAT 311, STAT 315. Calculus-based probability and statistics: distribution theory, estimation, hypothesis testing, applications to engineering and the sciences.
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3.00 Credits
Spring. Prerequisite: CS 156 or CS 160 or MATH 151 or MATH 152; MATH 155 or MATH 160. Probabilistic and stochastic models of real phenomena; distributions, expectations, correlations, averages; simple Markov chains and random walks.
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3.00 Credits
Spring, Summer. Prerequisite: STAT 301 or STAT 307/ERHS 307 or STAT 311 or STAT 315. Estimation and testing for linear, polynormal, and multiple regression models; analysis of residuals; selection of variables; nonlinear regression.
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3.00 Credits
Fall, Summer. Prerequisite: STAT 301 or STAT 307/ERHS 307 or STAT 311 or STAT 315. Analysis of variance, covariance; randomization; completely randomized, randomized block, latin-square, split-plot, factorial and other designs.
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3.00 Credits
Fall. Prerequisite: STAT 301 or STAT 307/ERHS 307 or STAT 311 or STAT 315. Data analysis principles and practice, statistical packages and computing; ANOVA, regression and categorical data methods.
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3.00 Credits
Fall. Prerequisite: MATH 255 or MATH 261. Probability, random variables, distribution functions, and expectations; joint and conditional distributions and expectations; transformations.
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3.00 Credits
Spring. Prerequisite: STAT 420. Theories and applications of estimation, testing, and confidence intervals, sampling distributions including normal, gamma, beta X-squared, t, and F.
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3.00 Credits
Fall, Spring, Summer. Prerequisite: STAT 340. Principles for multivariate estimation and testing; multivariate analysis of variance, discriminant analysis; principal components, factor analysis.
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