One-way Analysis of Variance

Week 4: September 15 & 17

MATH 417/GSR 517 ~ Statistical Applications ~ Fall 2003

Class meeting schedule and topics

Monday, September 15 ~	One-way Analysis of Variance
Wednesday, September 17 ~	More about the Analysis of Variance
Monday, September 22 ~	Multiple comparisons procedures
Wednesday, September 24 ~	Multiple comparisons and linear contrasts
Monday, September 29 ~	Review
Wednesday, October 1 ~	Test 1 (note date change)

Homework Assignments

5. Due Monday, September 15

   Required work

   • Read Chapter 5 on "Comparisons Among Several Samples"

   • If the first letter of your last name is "G," "K," or "S" please prepare a solution to Data Problem 31 on pages 81 and 82.
     If the first letter of your last name is "J," "N," or "W" please prepare a solution to Data Problem 32 on page 82.
     If the first letter of your last name is anything else, please prepare a solution to Data Problem 33 on page 82.

   • On a separate sheet of paper, write your answers to the following questions:

     If you were going to perform a study of the effectiveness of chapped lip treatments,

     1. Where would you go to find subjects to be in the study?
     2. What variable(s) would you measure to determine if a chapped lip treatment is effective or not?

   Optional work

   • Conceptual Exercises 1 through 19 on pages 75 through 77
   • Computational Exercise 30 on pages 80
   • Any of the other Data Problems selected from 31, 32, and 33 on pages 81 and 82

6. Due Wednesday, September 17

   Required work

   • Review Chapter 5 on "Comparisons Among Several Samples"
   • Computational Exercise 17 on page 142 (show all work)

   Optional work

   • Conceptual Exercises 1 through 12 on page 141
   • Computational Exercises 13 through 16 on pages 141 and 142

7. Due Monday, September 22

   Required work

   • Read Chapter 6 on "Linear Combinations and Multiple Comparisons of Means"
   • Data Problems 24 and 25 on pages 146 and 147
     Be sure to include graphs, descriptive statistics, parameters, hypotheses, test statistics, p-values, and in-context conclusions.

   Optional work

   • Computational Exercises 18 through 22 on pages 142 through 145
   • Data Problem 23 on pages 146