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Course Criteria
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3.00 Credits
Terminology, techniques, and management of Data Mining for biostatisticians.
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3.00 Credits
Data Analysis for biostatisticians in the biomedical and pharmaceutical fields.
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3.00 Credits
Introductions to the fundamentals of probability theory, random variables and their distributions, expectations, transformations of random variables, moment generating functions, special discrete and continuous distributions, multivariate distributions, order statistics, and sampling distributions.
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3.00 Credits
Statistical concepts applied to written and oral reports for consulting. For students majoring in statistics.
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3.00 Credits
Introduction to descriptive and inferential statistics. Topics may be selected from the following: descriptive statistics and graphs, probability, regression, correlation, tests of hypotheses, interval estimation, measurement, reliability, experimental design, analysis of variance, nonparametric methods, and multivariate methods.
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3.00 Credits
Introduction to probability theory. Fundamentals of probability theory, random variables, distribution and density functions, expectations, transformations of random variables, moment generating functions, convergence concepts, sampling distributions, and order statistics.
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3.00 Credits
Statistical methods of analyzing time series. Topics include autocorrelation function and spectrum, stationary and non stationary time series, linear filtering, trend elimination, forecasting, general models and auto regressive integrated moving average models with applications in economics and engineering.
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3.00 Credits
Introduction to the more common statistical concepts and methods. Interval estimation, tests of hypotheses, non-parametric methods, linear regression and correlation, categorical data analysis, design of experiments and analysis of variance, and the use of computer packages.
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3.00 Credits
Statistical methods and linear algebra. Theory and applications of simple and multiple regression models. Topics include review of statistical theory inference in regression, model selection, residual analysis, general linear regression model, multicollinearity, partial correlation coefficients, logistic regression, and other appropriate topics.
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3.00 Credits
Selected topics in Statistics. May be repeated once with change of topic.
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