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Course Criteria
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4.00 Credits
Generating functions and multivariate distributions. Conditioning. Chebyshev inequality and limit theorems. Multidimensional transformations of random variables. Derivation of t and F distributions. Uses of probability theory in mathematical statistics. Prerequisite: STAT 3401 or STAT 4412.
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4.00 Credits
Random variables, sampling distributions (binomial, Poisson, normal, exponential), conditional probability. Estimation, hypothesis testing. Computer-aided computations. Topics include: t-tests, correlation, regression; proportions, chi-squared; ANOVA. Prerequisite: MATH 1305.
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4.00 Credits
General linear hypothesis with emphasis on design and analysis of experiments. Data from science, engineering, and quality management. Factorial designs: random effects, nesting. Optional topics: incomplete blocks, missing data, analysis of covariance. Computer-aided analysis. Prerequisite: STAT 3502 or 3601.
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4.00 Credits
Detailed investigation of sampling methods. Design and comparisons of stratified, systematic, and cluster sampling procedures. Techniques of multistage and multiphase sampling. Emphasis on applications to social science. Prerequisite: STAT 1000 or equivalent.
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4.00 Credits
Basic probability rules (independence, Bayes' Theorem), distributions (binomial, Poisson, normal, exponential), reliability. Descriptive, inferential statistics (control charts, estimation, hypothesis testing: one, two samples), correlation, regression. Emphasizes: computer analysis, simulation; science, engineering applications. Prerequisite: MATH 1305. Not open to students with credit for STAT/ENGR 3502. Cross-listed with ENGR 3601.
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4.00 Credits
General linear model with emphasis on design and analysis of experiments. Fixed and random effects and nested models. Power and sample size considerations. Emphasizes: computer analysis, simulation; science, engineering applications. Prerequisite: STAT 3502 or STAT/ENGR 3601. Not open to those with credit for STAT 3503. Cross-listed with ENGR 3602.
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1.00 - 4.00 Credits
Supervised work experience in which student completes academic assignments integrated with off-campus paid or volunteer activities. Prerequisites: at least 2.0 GPA; departmental approval of activity. May be repeated for credit, for a maximum of 8 units. A maximum of 4 units will be accepted toward the Statistics major.
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4.00 Credits
Using computer packages (e.g., SPSS, SAS) and interpreting output. Data preparation, descriptive statistics, graphs, checks for normality, t-tests, F-tests, ANOVA, cross tabulations, chi-squared tests, correlation, and report preparation. Prerequisite: a previous course in statistics.
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4.00 Credits
Using program code in a statistical software package (e.g., SPSS, R or SAS), producing reformatted data and statistical analysis. Topics may include graphics, creating and managing data files, and simulations. Prerequisites: a previous Statistics course and skill in computer usage.
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4.00 Credits
Readings, discussion, and research on contemporary and/or significant issues in statistics. May be repeated for credit when content varies, for a maximum of 8 units.
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