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Course Criteria
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2.00 Credits
Seminar, 2 hours. Prerequisite(s): graduate standing. Theories of language and language acquisition which underlie modern methods of Spanish language teaching at the college level. Practical experience in grading, test construction, lesson planning, teaching techniques, effective aspects of teaching, and creativity in teaching. Graded Satisfactory (S) or No Credit (NC). Course is repeatable.
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1.00 - 4.00 Credits
Practicum, 3-12 hours. Prerequisite(s): CPLT 301 or equivalent; graduate standing; employment as a teaching assistant or associate in. Supervised teaching in lower-division courses. Required of all teaching assistants in Spanish. Graded Satisfactory (S) or No Credit (NC). Course is repeatable. The History Department offers these lower-division courses for the benefit of the entire campus, not specifically for History majors. HIST 010, HIST 015, HIST 017A, HIST 017B, and HIST 020 are appropriate preparation for upper-division work in the department.
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5.00 Credits
Lecture, 3 hours; discussion, 1 hour; laboratory, 3 hours. Prerequisite(s): CS 008 or equivalent; MATH 004 or MATH 005 or MATH 008A or MATH 009A or MATH 9HA or equivalent. An introduction to statistics using business applications. Topics include descriptive statistics, probability, discrete and continuous distributions, Bayes' theorem, random variables, estimation and confidence intervals, hypothesis testing, analysis of variance, and simple linear regression. Credit is awarded for only one of STAT 048 or STAT 100A.
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5.00 Credits
Lecture, 3 hours; discussion, 1 hour; laboratory, 3 hours. Prerequisite(s): MATH 005 or MATH 008A or MATH 009A or MATH 09HA or equivalent. A general introduction to descriptive and inferential statistics. Topics include histograms; descriptive statistics; probability; normal, binomial, and Poisson distributions; sampling distributions; hypothesis testing; and confidence intervals. Credit is awarded for only one of STAT 048 or STAT 100A.
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5.00 Credits
Lecture, 3 hours; discussion, 1 hour; laboratory, 3 hours. Prerequisite(s): STAT 100A. An introduction to inferential statistics. Topics include linear regression, correlation, analysis of variance, nonparametric methods, and simple experimental designs.
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4.00 Credits
Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): CS 008, MATH 023, or equivalents; upper-division standing. Survey of deterministic and probabilistic models for decision making. Topics include linear programming and extensions, networks, dynamic programming, decision trees, queuing models, and simulation. Uses of these models in decision making are discussed. Use of the computer is emphasized. Cross-listed with BUS 104.
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5.00 Credits
Lecture, 3 hours; discussion, 1 hour; laboratory, 3 hours. Prerequisite(s): STAT 100B or consent of instructor. Provides undergraduate students majoring or interested in life sciences with statistical tools for analyzing different types of data frequently encountered in life sciences. Emphasizes applications of methodology, including contingency table analysis, linear regression and ANOVA, maximum likelihood method and the estimation-maximization algorithm, logistic regression, Poisson regression, and survival analysis.
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4.00 Credits
Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 048 or STAT 100A or consent of instructor. Explores Deming's 14 points for management, graphical methods, fishbone diagram, Pareto analysis, control charts for attributes and variables, cusum and moving average charts, process-capability, economic design, acceptance sampling, Taguchi method, parameter design, tolerance design, reliability, hazard rate, censoring, and accelerated life testing. Cross-listed with BUS 127.
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4.00 Credits
Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 100A, STAT 100B, or equivalents. Simple random sampling. Stratified sampling. Cluster sampling. Ratio and regression estimates. Random response, capturerecapture and jack-knife techniques.
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4.00 Credits
Lecture, 3 hours; discussion, 1 hour. Prerequisite(s): STAT 100B or equivalent. Covers randomization tests, rank tests, methods of association, and distribution-free tests.
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