Online Master of Science in Applied Statistics Featured Courses
MA 5701 - STATISTICAL METHODS 3.0 CREDITS
Introduction to design, conduct, and analysis of statistical studies, with an introduction to statistical computing and preparation of statistical reports. Topics include design, descriptive, and graphical methods, probability models, parameter estimation and hypothesis testing.
MA 4720 - DESIGN AND ANALYSIS OF EXPERIMENTS 3.0 CREDITS
Covers construction and analysis of completely randomized, randomized block, incomplete block, Latin squares, factorial, fractional factorial, nested and split-plot designs. Also examines fixed, random and mixed effects models and multiple comparisons and contrasts. The SAS statistical package is an integral part of the course
MA 5761 - COMPUTATIONAL STATISTICS 3.0 CREDITS
Introduction to computationally intensive statistical methods. Topics include simulating random variables from probability distributions, Monte Carlo integration and variance reduction methods, Monte Carlo simulation methods, Bootstrap and jackknife, and permutation tests. This course will use the statistical software R.
Co-requisite: MA 4770 - Mathematical Statistics II
MA 5781 - TIME SERIES ANALYSIS AND FORECASTING 3.0 CREDITS
Statistical modeling and inference for analyzing experimental data that have been observed at different points in time. Topics include models for stationary and non-stationary time series, model specification, parametric estimation, model diagnostics and forecasting, seasonal models and time series regression models.
MA 5790 - PREDICTIVE MODELING 3.0 CREDITS
Application, construction, and evaluation of statistical models used for prediction and classification. Topics include data pre-processing, over-fitting and model tuning, linear and nonlinear regression models and linear and nonlinear classification models.
Pre-requisite: MA 4710 or MA 4720 or MA 4780
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