Statistics 401 A XM Handouts

Fall 2003

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Stat 401 A XM Home Page
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  1. Syllabus
  2. Computing Instructions
  3. Experiments vs. Observational Studies
  4. Five-Number Summary
  5. Histogram Matching
  6. Using Sample Data to Draw Conclusions about Population Means
  7. A Section 2.2 Practice Problem
  8. Comparing Two Means
  9. A Discussion of the t-Tool Assumptions
  10. An Analysis Using the Natural Log Transformation
  11. The Rank-Sum Test
  12. A Primer on Factorials and Combination Numbers
  13. The Sign Test and Wilcoxon Signed-Rank Test
  14. What test should I use?
  15. The One-Way Analysis of Variance F-Test
  16. The ANOVA Table and Comparison of Full and Reduced Models
  17. The Paper Airplane Experiment
  18. Linear Combinations of Means
  19. A Contrast that Tests for a Linear Trend
  20. Examination of Residuals in One-Way ANOVA (Crab Example)
  21. Adjustments for Multiple Testing and Estimation
  22. Adjustments for Multiple Testing and Estimation in SAS (Chicken Example)
  23. The Sample Linear Correlation Coefficient
  24. Introduction to the Least-Squares Regression Line
  25. Inference in Linear Regression
  26. Analysis of Variance for Simple Linear Regression
  27. SAS Code and Output for the Analysis of Minimum January Temperature vs. Latitude for 56 U.S. Cities (
  28. Estimation of Means and Prediction of Values in Simple Linear Regression
  29. Examining Residuals in Simple Linear Regression
  30. Interpreting the Slope of the Least-Squares Regression Line
  31. A Lack-of-Fit Test for Simple Linear Regression
  32. Introduction to Multiple Linear Regression
  33. SAS Code and Output to Accompany Introduction to Multiple Linear Regression
  34. Introduction to Indicator Variables and Interaction in Multiple Linear Regression
  35. SAS for Indicators and Interaction   Some Practice Problems to accompany the SAS Output
  36. Introduction to Two-Factor Analysis of Variance
  37. Introduction to Two-Factor Analysis of Variance (continued)
  38. Means vs. LSMeans and Type I vs. Type III Sums of Squares
  39. Randomized Complete Block Designs
  40. Re-analysis of the Airplane Data

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