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Course Criteria
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3.00 Credits
Pr. STA 271 or 352 or 552 or 580 Design and analysis of comparative studies. Completely randomized designs, blocking, factorials, random and mixed models, repeated measures designs. Computing sample size and power for designs.
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3.00 Credits
Pr. STA 291 or permission of instructor Planning and analysis of experimental and observational studies. Completely randomized, blocked, split-plot, and repeated measures designs. Factorial arrangements and interaction. Power and sample size calculation. (Alt Years)
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3.00 Credits
Pr. STA 352 or permission of instructor Estimation/removal of trend and seasonality, introduction to stationary stochastic processes, fitting ARMA/ARIMA models, forecasting techniques, miscellaneous topics, and introduction to a time series modeling software package. (Alt Years)
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3.00 Credits
Pr. grade of at least C in STA 290 and MAT 293 or permission of instructor Events and probabilities (sample spaces), dependent and independent events, random variables and probability distribution, expectation, moment generating functions, multivariate normal distribution, sampling distributions. (Fall)
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3.00 Credits
Pr. grade of at least C in STA 551 or permission of instructor Point estimation, hypothesis testing, confidence intervals, correlation and regression, small sample distributions. (Spring)
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3.00 Credits
Pr. STA 291 or 580 and knowledge of a scientific programming language Statistical methods requiring significant computing or specialized software. Simulation, randomization, bootstrap, Monte Carlo techniques; numerical optimization. Extensive computer programming involved. This course does not cover the use of statistical software packages. (Alt Fall)
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3.00 Credits
Pr. STA 291 or 352 or permission of instructor Methods for comparing time-to-event data, including parametric and nonparametric procedures for censored or truncated data, regression model diagnostics, group comparisons, and the use of relevant statistical computing packages. (Alt)
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3.00 Credits
Pr. 571 and 571L or permission of instructor Coreq. 572L Statistical methodology in research and use of statistical software. Regression, confidence intervals, hypothesis testing, design and analysis of experiments, one- and two-factor analysis of variance, multiple comparisons, hypothesis tests. (Spring)
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3.00 Credits
Pr. 571 and 571L or permission of instructor Coreq. 572 Using statistical software packages for data analysis. Problems parallel assignments in 572. (Spring)
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3.00 Credits
Pr. grade of at least C in 352 and MAT 310, or 662, or permission of instructor Linear regression, least squares, inference, hypothesis testing, matrix approach to multiple regression. Estimation, Gauss-Markov Theorem, confidence bounds, model testing, analysis of residuals, polynomial regression, indicator variables. (Fall)
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