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Course Criteria
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3.00 Credits
(3:3:0) Prerequisite: MATH 2350 or consent of instructor. Probability space, special families of distribution functions, expectations, conditional distributions, sampling distributions, point and interval estimation, hypothesis testing, distribution of functions of random variables, regression, nonparametric techniques
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3.00 Credits
(3:3:0) Prerequisite: MATH 2350 or consent of instructor. Probability space, special families of distribution functions, expectations, conditional distributions, sampling distributions, point and interval estimation, hypothesis testing, distribution of functions of random variables, regression, nonparametric techniques
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3.00 Credits
((3:3:0) Prerequisite: MATH 4343 or STAT 5329 or consent of instructor. Game theory, statistical decision, Bayesian statistics.
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3.00 Credits
(3:3:0) Prerequisite: STAT 5326 and 5329. Estimation and testing in linear regression, residual analysis, influence diagnostics, multicollinearity logistic regression, nonlinear regression.
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3.00 Credits
(3:3:0) Prerequisite: MATH 4343 or STAT 5329 or consent of instructor. Statistical inference, rank order statistics, chi-square and slippage tests, Kolmogorov and Smirnov type tests, confidence intervals and bands, runs tests, applications.
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3.00 Credits
(3:3:0) Prerequisite: MATH 4343 or STAT 5329 Principles of design and analysis of experiments, Latin squares, split plots, incomplete block designs, efficiency.
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3.00 Credits
(3:3:0) Prerequisite: MATH 4343 or STAT 5329. Multivariate normal, convariance matrix and operations, distribution of quadratic forms, general linear hypothesis of full and non-full rank, specific linear models.
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3.00 Credits
(3:3:0) Prerequisite: STAT 5329 or consent of instructor. Multivariate normal distribution, estimation of the mean vector and covariance matrix, distribution of sample correlation coefficients, the generalized T2 statistic, classification, distribution of the sample covariance matrix.
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3.00 Credits
(3:3:0) Prerequisite: MATH 4343 or STAT 5329 or consent of instructor. Applied regression analysis, cluster analysis, factor analysis, modeling, special topics in designs, sensitivity analysis, non-linear estimation. May be repeated for credit.
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3.00 Credits
(3:3:0) Prerequisite: MATH 4343 or STAT 5329. Theory of simple random sampling, stratified random sampling, cluster sampling, ratio estimates, regression estimates, other sampling methods.
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