STAT 5210 A (CRN: 15611)
Statistics: Advanced Stat Methods & Theory
3 Credit Hours—Seats Available!
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About STAT 5210 A
Parametric and non-parametric two-sample tests. Multiple regression and correlation. Matrix representations. Basic experimental design. Analysis of variance (fixed, random, and mixed models). Statistical Software usage. Credit not awarded for both STAT 5210 and STAT 3210. Prerequisites: Graduate student or Instructor permission; content knowledge of STAT 2830 assumed.
Notes
Graduate student or Instructor permission; Content knowledge of STAT 2830 assumed; PACE students with permission and override; Co-located with STAT 3210; Total combined enrollment: 40
Section Description
This will be a primarily flipped class, where you will be responsible for reading the textbook and class materials before working on the material in class. This pre-class work will be essential to your class work each day. We will use R statistical software. The course will not include teaching R. A basic knowledge of R is expected. Key topics are: *Straight-Line Regression Analysis *The Correlation Coefficient and Regression Analysis *The Analysis of Variance (ANOVA) Table *Multiple Regression Analysis: General Considerations *Testing Hypothesis in Multiple Regression *Correlations: Multiple, Partial, and Multiple Partial *Confounding and Interaction *Regression Diagnostics *One-Way ANOVA *Two-Way ANOVA
Section Expectation
Students should expect three or more hours of work outside of class for every hour of class time. Reading the textbook and class notes before each class is essential. Homework assignments will be listed on the Brightspace class webpage. Late assignments will not be accepted. The course will consist of a mixture of short lectures, problem solving, in-class group work, discussion, and projects to highlight particular topics. It would be impossible, however, for these to encompass all of the material for the course. There will be material in the text for which you will be responsible that we will not cover in detail during class. You must read the material in the text before we discuss it in class.
Evaluation
Final grades will be determined by exams, R labs, quizzes, homework, and participation in class discussions.
Important Dates
Note: These dates may not be accurate for select courses during the Summer Session.
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