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Course Criteria
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0.00 - 4.00 Credits
Credit and title to be arranged. This course is to be used on a limited basis to offer developing subject matter areas not covered in existing courses. (Courses limited to two offerings under one title within two academic years).
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0.00 - 4.00 Credits
(Prerequisite: ACT math subscore 24, or grade of C or better in MA 1313 ). Two hours lecture, Two hours laboratory. Basic concepts and methods of statistics, including descriptive statistics, probability random variables, sampling distribution, estimation, hypothesis testing, introduction to analysis of variance, simple linear regression. (Same as MA 3123),
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0.00 - 4.00 Credits
Hours and credits to be arranged.
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0.00 - 4.00 Credits
One hour lecture. Introduction to the statistical computer packages available at MSU.
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0.00 - 4.00 Credits
(Prerequisite: Consent of the Director of the Center for Statistical and Mathematical Services). (May be repeated for credit.) Provides students with the opportunity to participate as statistical consultants on real projects; consultants are required to attend a weekly staff meeting.
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0.00 - 4.00 Credits
(Prerequisite: An introductory course in statistical methods). Three hours lecture. Nonparametric and distribution-free methods, including inferences for proportions, contingency table analysis, goodness of fit tests, statistical methods based on rank order, and measures of association.
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0.00 - 4.00 Credits
(Prerequisite:MA 2743, Corequisite MA 3113). Three hours lecture. Data description and descriptive statistics, probability and probability descriptions, parametric one-sample and two-sample inference procedures, simple linear regression, one-way ANOVA. Use of SAS. (Same as MA 4243/6243).
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0.00 - 4.00 Credits
(Prerequisite:MA/ST 4243/6243 and MA 3113). Three hours lecture. Multiple linear regression fixed, mixed, and random effect models;block design;two-factor analysis of variance;three-factor analysis of variance; analysis of covariance. Use of SAS. (Same as MA 4253/6253)
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0.00 - 4.00 Credits
(Prerequisite: Grade of C or better in ST 3113,or equivalent). Two hours lecture, Two hours laboratory. Spatial data analysis;kriging, block kriging, cokriging, variogram models;median polish and universal kriging for mean-nonstationary data;spatial autoregressive models; estimation and testing;spatial sampling.
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0.00 - 4.00 Credits
(Prerequisite: MA 2733). Three hours lecture. Basic concepts of probability, conditional probability, independence, random variables, discrete and continuous probability distributions, moment generating function, moments, special distributions, central limit theorem. (Same as MA 4523/6523).
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