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Course Criteria
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3.00 Credits
Working with a faculty mentor, students develop a research project and related research skills. FS: 06/04/2014. CL: 2020.
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3.00 Credits
A senior thesis related to one of the advanced courses in the major program. Prerequisite: minimum GPA of 3.50 in major courses, 3.30 overall. CL: 2020.
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3.00 Credits
A course in statistical literacy. Topics include data sources and sampling, concepts of experimental design, graphical and numerical data description, measuring association for continuous and categorical variables, introduction to probability and statistical inference, and use of appropriate software. Credit given only for STAT 110 or STAT 112. CL: 2020.
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3.00 Credits
Statistics and the Media. (3) Statistical and information literacy. Experimental and survey design; descriptive statistics; basic probability; simple confidence intervals and hypothesis tests; statistical software; collection, management, and evaluation of information; and presentation of statistics in the media. Credit given for only STAT 110 or STAT 112. FS: 11/1/2017. CL: 2020.
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3.00 Credits
Introduction to the fundamentals of modern statistical methods, including descriptive statistics, probability, random sampling, simple linear regression, correlation, tests of hypotheses, and estimation. Prerequisite: MATH 111 or MATH 115 or STAT 110. CL: 2020.
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3.00 Credits
Introduction to fundamental statistical methods with applications in the biological and life sciences. Includes descriptive statistics; probability; one and two-sample models for population means; contingency tables (including relative risk, odds ratios, case-control studies, and estimation of sensitivity and specificity); linear regression; logistic regression; aspects of survival analysis, and ANOVA. Prerequisite: MATH 111 or higher. FS: 06/06/2018. CL: 2020.
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3.00 Credits
Fundamental statistical methods with applications in business. Includes descriptive statistics, graphical methods, probability, distributions, sampling, inference, contingency tables, and linear regression. Prerequisite: MATH 111 or higher. FS: 12/04/2019. CL: 2020.
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3.00 Credits
A second course in statistical methods. Multiple linear regression, model building and regularization, one-way ANOVA, multiple comparisons, and introductions to the ideas of experimental design and generalized linear models. Focused on choosing correct methods, conceptual understanding, using statistical software, checking assumptions, and practical implications. May not be taken concurrently with or after STAT 516. Prerequisite: C or better in STAT 201, STAT 205, STAT 206, PSYC 220 or SOCY 392. FS: 06/07/2023.
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3.00 Credits
Contract approved by instructor, advisor, and department chair is required for undergraduate students.
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3.00 Credits
This course introduces concepts, connections, and evolving relationships among the sciences engineering and mathematics to strengthen understanding of current ideas and applications of advancing technologies.
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