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Course Criteria
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3.00 Credits
(3 credits)(Prereq: STAT*201, CBAD*291, or PSYC*225 with a grade of 'C' or better) An in-depth coverage of regression analysis suitable as a second course in statistics. Topics include correlation, simple and multiple linear regression, method of least squares, model selection and diagnostic checking, hypothesis testing, outliers, influence, multicollinearity, transformations, and categorical regressors. Computers and statistical software used extensively. F, even years
Prerequisite:
Take STAT*201 CBAD*291 PSYC*225(7824) or PSYC*225(PSYC_225); Minimum grade C;
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3.00 Credits
(3)(Prereq: STAT 201, CBAD 291 or PSYC 225 with a grade of C or better) This course offers in depth coverage of one and two way ANOVA. Topics include model statements, assumption checks and remedial measures, inference for factor level and treatment level means, inference for contrasts and multiple testing, and treatment of interaction terms. Computers and statistical software will be used extensively.F.
Prerequisite:
Take STAT*201 CBAD*291 PSYC*225(7824) or PSYC*225(PSYC_225); Minimum grade C;
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3.00 Credits
(3 credits)(Prereq: STAT*201, CBAD*201, or PHYS*225 with a grade of C or better) This course covers a variety of statistical concepts and methods. Topics include interference for means and proportions using both parametric and non-parametric approaches, a detailed study of simple linear regression, and analysis of variance (ANOVA). Examples are drawn from various fields of study and statistical software is utilized for analyses. S
Prerequisite:
Take STAT*201 CBAD*291 PSYC*225(7824) or PSYC*225(PSYC_225); Minimum grade C;
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3.00 Credits
A first course in the analysis of discrete data including two-dimensional tables, the log linear model, goodness-of-fit of the model, measures of dependence, three and higher dimensional tables, hierarchical models, model selection,ordered categories, logit model, and introduction to Bayesian analysis of categorical data. Computers and statistical software will be used extensively.
Prerequisite:
Take STAT*201 CBAD*291 PSYC*225(7824) or PSYC*225(PSYC_225); Minimum grade C;
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2.00 Credits
(2 credits)(Prereq: STAT*316 with a grade of C or better and STAT*318 with a grade of C or better and at least two other 300-level statistics classes with a C or better) Students syntesize information across many statistical methods through case studies. For each case study, students must determine the most appropriate approach to answer the researcher's questions using statistics. Students present their analysis and conclusions in a series of written and oral presentations. S
Prerequisite:
GROUP: Take STAT*316(6193) STAT*318(4806); Minimum grade C; GROUP: Take 2 courses; Minimum grade C; From Subject STAT; From Levels 3RDYEAR 4THYEAR; Except courses STAT*316(6193) STAT*318(4806);
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3.00 Credits
(3 credits)(Prereq: A grade of 'C' or better in MATH*161 or MATH*161B) Sample spaces, probability, randon variables, distributions.
Prerequisite:
Take MATH*161 or MATH*161B; Minimum grade C;
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3.00 Credits
Point and interval estimation, test of hypotheses, sufficiency, limiting distributions and order statistics.
Prerequisite:
Take STAT*412; Minimum grade C;
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3.00 Credits
(3 credits)(Prereq: a grade of C or better in STAT*412) This course is an introduction to models and graphical anaylses for data, which are generated sequentially. Topics include basic models (white noise, AR, random walks), time series regression and forecasting. Extensive use of software. F, even years
Prerequisite:
Take STAT*412; Minimum grade C;
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3.00 Credits
(3 credits)(Prereq: a grade of C or better in STAT*412) This course presents an in-depth introduction to the Bayesian paradigm. A study of Bayes' Rule introduces students to likelihood functions, posterior and prior distributions. Bayesian inference including proportions, means and regression are explored in comparison to the frequentist approach. Extensive use of software. S, even years
Prerequisite:
Take STAT*412; Minimum grade C;
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3.00 Credits
(3 credits) An introduction to the basic concepts and understanding of sustainability locally and globally. Topics focus around the three pillars of sustainability; environment, economic and social, as well as topics such as waste reduction, consumer choices, energy, transportation, and natural resources. The field of sustainability continues to evolve, especially as awareness spreads about scarce resources on a crowded planet. Students explore sustainability through experiential learning activities and create a research-based presentation. F,S,Su
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