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Course Criteria
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3.00 Credits
Prerequisite: MAS 3105 and STA 4321. This is the first in a two-term sequence in statistical methods. This course is a blend of the theory and applications of regression analysis and of the design and analysis of data. It focuses on linear regression with one predictor variable, inferences involving regression coefficients and correlation analysis, diagnostics and remedial measures, multiple linear regressions and its diagnostics, and an introduction to the analysis of variance. Emphasis is placed on the application of these techniques to data and interpretation of the results. The course uses the statistical analysis software (SAS) for data analysis.
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3.00 Credits
Prerequisite: STA 6166. This is the second in a two-term sequence in statistical methods. In this course, the focus is exploration of multiple regression (including model building, diagnostics, and remedial measures), multifactor studies using analysis of variance and covariance, and other topics in the analysis of categorical or multivariate data. The course uses the statistical analysis software (SAS) for data analysis.
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3.00 Credits
Prerequisite: MAA 4211 and STA 4321. This is the first in a two-term sequence in mathematical statistics. It covers topics such as probability, random variables, expected values, sampling distributions, Central Limit Theorem, estimation, properties of estimators, and order statistics.
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3.00 Credits
Prerequisites: MAS 3105, MAA 4211 and STA 4321 This is a course in advanced topics in probability. It covers probability distributions, conditional probability and conditional expectations. Some of the fundamental stochastic processes (Markov chains, the Poisson process, Renewal Theory, Brownian motion) will be covered.
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3.00 Credits
Prerequisite: Permission of the department. This course covers the statistical properties, as well as the design, implementation, and operation, of various statistical process control (SPC) schemes including those based on Shewhart, cumulative sum, and moving average control charts. Methods appropriate for conducting a capability study will also be covered. The role of SPC in process improvement will be examined, as well as statistical models useful in quality control. Additional selected topics such as acceptance sampling will be presented as time permits. The statistical analysis software SAS will be used extensively.
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3.00 Credits
Prerequisite: MAS 3105, STA 6166. This course introduces a range of multivariate methods used for analyzing complex data sets with large numbers of variables. The following topics will be covered: multivariate analysis of variance, correlation, discriminant analysis, and factor analysis.
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1.00 - 3.00 Credits
Prerequisite: Permission of the department. May be repeated for 9 credits under different topics.
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3.00 Credits
Prerequisite: STA 2014 or equivalent. This course is a general introduction to research methods in the social sciences, with emphasis on theory, measurement, research design, data collection and the ethics of research.
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3.00 Credits
PREREQ: SYA 3300. This course provides an overview of qualitative methods used in sociological research, including participant observation, interviews and archival research. Students will read exemplary studies, practice methods first hand, and learn how to use qualitative data to support an argument. Throughout the course we will discuss standards of ethical research.
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3.00 Credits
PREREQ: SYA 3300. This course introduces students to quantitative analysis of social scientific data. The course is designed to teach students how to manage, apply, interpret, and compute quantitative data from both primary and secondary sources. The course will involve substantial usage of computerized analytical techniques.
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