STA 6207
Section 8907, Fall 2008

Course Information and Policies Sheet (PDF) SAS® and R Software Access and Information
Assignments Course Notes and Resources
Data Examples in SAS® Code Data Examples in R Code

Announcements:

Course Textbook Instructor: Teaching Assistant:
Trevor Park
116C Griffin-Floyd Hall
tpark@stat.ufl.edu
Phone: 273-2973
Fax: 392-5175
Jihyun Song
209 Griffin-Floyd Hall
Office Hours Office Hours
Monday4 - 5 PM 10:50 - 11:40 AM
Tuesday 10:50 - 11:40 AM
Wednesday10:45 - 11:45 AM
Thursday
Friday3 - 4 PM

Class Schedule:

December 18: FINAL EXAM — 10:00 AM — Griffin-Floyd 100 up to logistic regression
 
December 10: Logistic Regression [15.5] HW 10 Due
December 8: Logistic Regression [15.5]
December 5: Generalized Least Squares 12.5.2
December 3: Weighted Least Squares; Generalized Least Squares 12.5.1-12.5.2 HW 9 Due
December 1: Weighted Least Squares 12.5-12.5.1 HW 10 Posted
November 26: Box-Cox Transformations 12.4
November 24: Transformations: Variance Stabilizing [12.2], 12.3
November 21: Transformation of Variables 12.1-12.2 HW 8 Due; HW 9 Posted
November 19: Regression Diagnostics 11.2.2-11.2.5, 11.3.2, 11.4.2, [11.4.3]
November 17: Regression Diagnostics 11.1.5-11.2.1, 11.4.1-11.4.2
November 14: Regression Diagnostics 11.1-11.1.5, 11.4-11.4.1
 
November 12: MIDTERM 2 — 7:30 PM — Griffin-Floyd 100 up to 8.1
 
November 12: Difficulties with Linear Least Squares 10.1-10.6, [10.7] HW 8 Posted
November 10: Trigonometric Regression Models, Polynomial Response Surfaces 8.2-8.3 HW 7 Due
November 7: Orthogonal Polynomials, Trigonometric Regression Models 8.1-8.2
November 5: Polynomial Regression: Lack of Fit, Orthogonal Polynomials 8.1
November 3: Polynomial Regression 8.1
October 31: Lack-of-Fit Tests; Polynomial Regression 4.7; 8.1 HW 6 Due; HW 7 Posted
October 29: Homogeneity of Regressions; Lack-of-Fit Tests 9.6; 4.7
October 27: Two-Way Model, Homogeneity of Regressions 9.5-9.6
October 22: One-Way ANOVA, Two-Way Model 9.3.4, 9.5 HW 5 Due; HW 6 Posted
October 20: One-Way Model: Means and Effects 9.2-9.3.3
October 17: Variable Selection; Class Variables: One-Way Model 7.6; 9.1-9.2
 
October 15: MIDTERM 1 — 7:30 PM — Griffin-Floyd 100 up to 4.5.4
 
October 15: Variable Selection 7.4-7.6
October 13: Variable Selection 7.1-7.3, 7.5 HW 4 Due; HW 5 Posted
October 10: Case Study: Spartina Biomass 5.2.1-5.5
October 8: Simultaneous (Joint) Inference: Bonferroni, Scheffé, Confidence Regions; Case Study: Spartina Biomass 4.6; 5.1-5.2.1
October 6: Dropping Model Terms and R-Notation, Simultaneous (Joint) Inference 4.5.5-4.6
October 3: The GLH F-Test Using a Reduced Model, Linear Reduced Models, Dropping Model Terms 4.5.4-4.5.5
October 1: General Linear Hypothesis t-Tests, Testing the GLH with Reduced Models 4.5.2-4.5.4 HW 3 Due; HW 4 Posted
September 29: t-Statistics, Tests, and Confidence Intervals, The General Linear Hypothesis 4.5.1-4.5.2
September 26: Distribution of Quadratic Forms: F-Statistics and Tests 4.4
September 24: Analysis of Variance, Variance Estimates, Expected Quadratic Forms 4.2-4.3
September 22: Normality of New Predictions; Quadratic Forms and Sums of Squares 3.5; 4.1-4.2 HW 2 Due; HW 3 Posted
September 19: Means and Variances in Regression, Normality Assumptions 3.4-3.5
September 17: Predicted Values and Residuals, Random Matrices and Vectors 3.3-3.4
September 15: Matrix Formulation of Linear Regression and Least Squares, Predicted Values 3.1-3.3
September 12: Overview of Matrices 2.3-2.6 HW 1 Due; HW 2 Posted
September 10: Overview of Matrices 2.1-2.4
September 8: Confidence Intervals, Prediction Intervals, Regression Through the Origin, Several Independent Variables 1.6-1.8
September 5: Prediction Error, Significance Tests 1.5-1.6
September 3: Precision of Estimates, Prediction Error 1.5 HW 1 Posted
August 29: ANOVA Quantities 1.4
August 27: Simple Linear Regression: Model, Least Squares, Analysis of Variance 1.1-1.4
August 25: Introduction

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