MGS 9950 / Regression Analysis |
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Welcome to the web site for Ed Rigdon's Regression Analysis course, MGS 9950, at Georgia State University. Check here for announcements related to the course. (Feedback.) Here are links to the ICPSR site, their data browsing page, and specific links to the ACSI and plant location datasets. Class 1 (Jan. 8) classnote, plus project guidelines and information sheet. Class 2 (Jan. 10) classnote plus (corrected) spreadsheet, and a Java applet that demonstrates some of the differences between OLS and LAD estimation. Class 3 (Jan. 15) classnote, spreadsheet, first homework assignment and data set. Class 4 (Jan. 22) classnote. Class 5 (Jan. 24) classnote and homework #2 assignment and data set. Class 6 (Jan. 29) classnote. Class 7 (Jan. 31) classnote, link to the Anscombe graphs, a note about jittering in SPSS, homework #3 assignment and data set, jittering example dataset. Class 8 (Feb. 5) classnote. Class 9 (Feb. 7) classnote, homework #4 assignment and dataset. Class 10 (Feb. 12) classnote. Class 11 (Feb. 14) classnote and homework #5 assignment (same data as last week). Class 12 (Feb 19), we will review homework, finish talking about nonlinear transformations, then start our midterm review. Class 13 (Feb. 21) continued our midterm review. Class 14 (Feb. 26) was project time. Class 15 (Feb. 28) was our midterm exam. Class 16 (March 11) classnote on interactions. Class 17 (March 13) classnote on interactions (part 2) with the spreadsheet demonstrating simple regression line calculations for the fish data, plus homework #6 and the dataset. Class 18 (March 18) classnote on categorical predictor variables. Class 19 (March 20) continuing our discussion of categorical predictors, with a new homework #7 assignment, using the fish data. Class 20-21 (March 25-27) classnote on interactions with categorical (and continuous) predictors; homework #8 assignment (using last week's data). Class 22 (April 1) classnote on outlier diagnostics (no, really . . . trust me). Class 23 (April 3) classnote on collinearity, homework #9 assignment and data set. Class 24-25 (April 8-10) classnote on logistic regression, an example dataset, some background info, and example output in both .spo and .htm formats. Class 26 (April 15) will finish up last week's material, then look at extensions to logistic regression. Class 27 (April 17) final exam review. Classes 28-29 (April 22-24) will feature term project presentations: Tuesday, April 22: Guillory; Olsen-Ruiz-Scott; Nguyen-Pleasant-Weaver. Thursday, April 24: Beckman-Raymond; Bissah-Bovell; Edwards-Hawkins-Tidwell. . |
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