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Course Criteria
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:Mathematics 21A, B, C, and D. Fundamental concepts of probability theory, discrete and continuous random variables, standard distributions, moments and moment-generating functions, laws of large numbers and the central limit theorem. Not open for credit to students who have completed Mathematics 135A.-I, II, III. (I, II, III.) Mueller
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:course 131A or Mathematics 135A. Sampling, methods of estimation, sampling distributions, confidence intervals, testing hypotheses, linear regression, analysis of variance, elements of large sample theory and nonparametric inference.-II, III. (II, III.) Mueller
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:course 131B. Sampling, methods of estimation, sampling distributions, confidence intervals, testing hypotheses, linear regression, analysis of variance, elements of large sample theory and nonparametric inference.-III. (III.) Mueller
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:course 103 and Mathematics 16B, or the equivalents; no credit will be given to students majoring in Statistics. Probability, basic properties; discrete and continuous random variables (binomial, normal, t, chi-square); expectation and variance of a random variable; bivariate random variables (bivariate normal); sampling distributions; central limit theorem; estimation, maximum likelihood principle; basics of hypotheses testing (one-sample).-I. (I.)
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:course 130B, and preferably course 131B. Multivariate normal distribution; Mahalanobis distance; sampling distributions of the mean vector and covariance matrix; Hotelling's T2; simultaneous inference; one-way MANOVA; discriminant analysis; principal components; canonical correlation; factor analysis. Intensive use of computer analyses and real data sets.-III. (III.)
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4.00 Credits
Lecture-3 hours; term paper. Prerequisite: course 108 or the equivalent. Time series relationships, cyclical behavior, periodicity, spectral analysis, coherence, filtering, regression, ARIMA and statespace models; Applications to data from economics, engineering, medicine environment using time series software.-III. (III.)
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:course 130B or 131B, or courses 106 and 108. Varieties of categorical data, cross-classifications, contingency tables, tests for independence. Multidimensional tables and log-linear models, maximum likelihood estimation; tests of goodness-of-fit. Logit models, linear logistic models. Analysis of incomplete tables. Packaged computer programs, analysis of real data. GE credit: SciEng.-I. (I.)
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4.00 Credits
Lecture-1.5 hours; web virtual lecture-5 hours.Prerequisite: two years of high school algebra or the equivalent in college. Descriptive statistics; basic probability concepts; binomial, normal, Student's t, and chi-square distributions. Hypothesis testing and confidence intervals for one and two means and proportions. Regression. Not open for credit to students who have completed course 13 or higher. GE credit: SciEng.-I. (I.)
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4.00 Credits
Lecture-3 hours; laboratory-1 hour. Prerequisite:course 130A or 131A, and one of courses 13, 32, 100, 102, or the equivalent, and experience in computer programming; course 130B or 131B recommended. Use of computers in statistics. Numerical foundations of statistical procedures. Computation of probabilities and quantiles. Random numbers. Monte Carlo method and bootstrap. Methods for parametric statistical models. Graphical methods and exploratory data analysis.-II. (II.)
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4.00 Credits
Lecture-3 hours; discussion/laboratory-1 hour.Prerequisite: course 130B or 131B or consent of instructor. Stochastic modeling and inference for reliability systems. Topics include coherent systems, statistical failure models, notions of aging, maintenance policies and their optimization. Offered in alternate years.
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