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Course Criteria
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:two years of high school algebra, and upper division standing. Introductory probability and statistics at a rigorous yet precalculus level. Rigorous precalculus introduction to probability and parametric/ nonparametric statistical inference with computing; binomial, Poisson, geometric, normal, and sampling distributions; exploratory data analysis; regression analysis; ANOVA. Only two units of credit allowed to students who have taken course 32. Not open for credit to students who have taken course 100. GE credit: SciEng.-I, III. (I, III.)
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:course 13, 32, or 102; and Mathematics 16A, 16B. Descriptive statistics; probability; random variables; expectation; binomial, normal, Poisson, other univariate distributions; joint distributions; sampling distributions, central limit theorem; properties of estimators; linear combinations of random variables; testing and estimation; Minitab computing package. GE credit: SciEng.-I, II, III. (I, II, III.)
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4.00 Credits
Lecture-3 hours; laboratory-1 hour. Prerequisite:course 13, 32, or 102. Sign and Wilcoxon tests, Walsh averages. Two-sample procedures. Inferences concerning scale. Kruskal-Wallis test. Measures of association. Chi square and Kolmogorov-Smirnov tests. Offered in alternate years. GE credit: Sci- Eng.-(II.)
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4.00 Credits
Lecture-4 hours. Prerequisite: course 13, 32, or 102. One-way and two-way fixed effects analysis of variance models. Randomized complete and incomplete block design, Latin squares. Multiple comparisons procedures. One-way random effects model. GE credit: SciEng.-I, II. (I, II.)
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:course 13, 32 or 102. Simple linear regression, variable selection techniques, stepwise regression, analysis of covariance, influence measures, computing packages. GE credit: SciEng.-I, II, III. (I, II, III.)
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4.00 Credits
Lecture-3 hours; laboratory-1 hour. Prerequisite:two years of high school algebra. Random experiments; countable sample spaces; elementary probability axioms; counting formulas; conditional probability; independence; Bayes theorem; expectation; gambling problems; binomial, hypergeometric, Poisson, geometric, negative binomial and multinomial models; limiting distributions; Markov chains. Applications in the social, biological, and engineering sciences. Offered in alternate years. GE credit: SciEng.
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:Mathematics 21A, B, C, and D. Basic concepts of probability theory with applications to electrical engineering, discrete and continuous random variables, conditional probability, combinatorics, bivariate distributions, transformation or random variables, law of large numbers, central limit theorem, and approximations. No credit for students who have completed course 131A or Civil and Environmental Engineering 114. GE credit: SciEng.-I, III. (I, III.) Mueller
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4.00 Credits
Lecture-3 hours; discussion-1 hour. 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 13V or higher. GE credit: Sci- Eng.-I, II, III. (I, II, III.)
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:Mathematics16B. Basic probability, densities and distributions, mean, variance, covariance, Chebyshev's inequality, some special distributions, sampling distributions, central limit theorem and law of large numbers, point estimation, some methods of estimation, interval estimation, confidence intervals for certain quantities, computing sample sizes. Only 2 units of credit allowed to students who have taken course 131A.-I. (I.)
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4.00 Credits
Lecture-3 hours; discussion-1 hour. Prerequisite:course 130A. Transformed random variables, large sample properties of estimates. Basic ideas of hypotheses testing, likelihood ratio tests, goodnessof- fit tests. General linear model, least squares estimates, Gauss-Markov theorem. Analysis of variance, F-test. Regression and correlation, multiple regression. Selected topics.-II. (II.)
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