| Title | APPLIED REGRESSION ANALYSIS |
| Department | STA |
| Course Number | 242 |
| Professor | MACKENZIE, G |
| Crosslisted as | ENV255-01 ENV255-02 ENV255-03 ENV255-04 |
| Course Homepage | www.stat.duke.edu/courses/ |
| Prerequisites |
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| STA 210 or equivalent. |
| Synopsis of course content |
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| This course covers linear and multiple regression with diagnostics. Polynomial regression and analysis of variance are special cases (ANOVA). The aim will be mostly applied rather than theoretical. We will also cover other commonly used regression techniques such as logistic regression, local regression (LOESS), robust regression, and perhaps spline regression. Software will be used liberally throughout. |
| Textbooks |
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| Regression with Graphics: A Second Course in Applied Statistics, Lawrence Hamilton. |
| Assignments |
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| Weekly homework due before class on Thursdays and computer labs. You are encouraged to work together in pairs. |
| Exams |
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| Two midterms (Feb 11, Mar 11) and a final (May 6, 9am-12pm). |
| Term Papers |
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| Small groups of students will perform one final data analysis on a data set chosen from a collection of provided data sets. |
| Grade to be based on |
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| 50% Homework, 10% on final term paper, and 40% on exams. |