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BIST 511 - Statistical Inference |

This course will introduce the basics of statistical inference, parameter estimation, and hypothesis testing in preparation for more in depth coverage of specific models in later courses. Inference procedures: point and interval estimation, sufficient statistics, hypothesis testing, methods of constructing test and estimation procedures. Point estimation: criteria for estimators, maximum likelihood estimators, Bayes estimators, mean square error, unbiased estimators, asymptotic variance of estimators. Hypothesis testing: error probabilities, power function, one-sample inference about the mean with known and unknown variance, comparison of two samples, 2×2 contingency tables, shortcuts and non-parametric methods. Modeling and study design: missing data, extreme observations, transformations, factorial experiments, probability sampling, sample size, two-stage sampling, stratified sampling, nonsampling errors. 3.000 Credit hours 3.000 Lecture hours 0.000 Lab hours Levels: MN or MC Graduate, Undergraduate Schedule Types: Lecture Biostatistics & Epidemiology Department Restrictions: Must be enrolled in one of the following Levels: MN or MC Graduate Must be enrolled in one of the following Majors: Biostatistics Biostatistics Mathematics and Statistics |

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