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**Before Wednesday, August 27**- Read the first page and a half of the
*Preface*. Also read pages 1 through 15 of Chapter 1. Many of these concepts are likely to seem new to you even if you have recently taken a statistics course. There are several important ideas in this material. Section 1.3.2 is particularly important. Click here to see a simple example that might help you better understand the mechanics of computing a p-value for a randomization test.

**Before Friday, August 29**- Read pages 15 through 22. Also read the
*Conceptual Exercises*on pages 22 through 24. You should be able to make a rough histogram, a stem-and-leaf diagram, and a boxplot by hand if given a simple set of data. You should be able to compute a five-number summary, average, and standard deviation for a set of numbers.

**Before Wednesday, September 3**- Read pages 28 through 37. These pages are packed with a lot of important concepts. Try hard to understand everything. This will take awhile.
- Note that in Display 2.6 there should be an n under the square root sign in step 2.
- Click here to see a simple example that might help you better understand the concept of standard error.
- Many students want to know why we look up 0.975 in the t-table as part of the computation of a 95% confidence interval. After you have done the reading, click here to see a somewhat technical explanation.

**Before Friday, September 5**-
Review Wednesday's reading assignment.

**Before Monday, September 8**-
Read pages 37 through 51. In Diplay 2.10 on page 44, the bubble that says "From Display 2.7" should read "From Display 2.8".

**Before Wednesday, September 10**-
Review Monday's reading assignment.

**Before Friday, September 12**-
Read pages 56-68. Pay particular attention to the concepts covered in Displays 3.4 through 3.7.

**Before Monday, September 15**-
Read pages 68-76. On page 70 after "(and since the log preserves the
ordering)" the equation should read Median[log(Y)]=log[Median(Y)].

**Before Wednesday, September 17**-
Read pages 85-95.

**Before Friday, September 19**-
Read pages 95-98.
- You can see a primer on factorials and combination numbers by clicking here.
- The text describes a permutation test for the O-ring data that uses the two-sample
*t*-statistic. In class we will see how the same result can be obtained using the difference in sample averages as the test statistic rather than the two-sample*t*-statistic. Using the difference in sample averages rather than the*t*-statistic is simpler and valid; however, the results for the two approaches are not always the same. - We will not discuss the Welch
*t*-test or the Satterthwaite approximation for degrees of freedom in class. Those of you taking Stat 402 will see the Satterthwaite method for approximating degrees of freedom next semester. SAS's*proc ttest*automatically provides output for the Welch*t*-test under the output for the pooled*t*-test that we have discussed extensively.

**Before Monday, September 22**-
Read pages 99-105. Please read the Conceptual Exercises and their solutions also. We will not discuss Section 4.5 in class. Sections 4.5.1 and 4.5.2 are important. It is also good to know about the material in Sections 4.5.3 and 4.5.4, but I will not
ask you any questions about this material in homework or exams.

**Before Wednesday, September 24**-
Begin your review for Exam 1 which will take place in the lab on September 29. Exam 1 covers material discussed in Chapters 1 through 4 of the text.

**Before Wednesday, October 1**-
Read pages 113-127.

**Before Friday, October 3**-
Read Sections 5.5, 5.6.1, 5.6.4, and 5.7. When reading 5.7, don't worry about the details of the Spock trial study. Also try Conceptual Exercises 2-4 and 7-12. Note that we are skipping a few sections including Section 5.6.2. Section 5.6.2 talks about
a rank-based method that is a generalization of the rank-sum test to the case of more than two groups. I want you to know that such a method exists in case you ever need to use it in your research, but we won't work with it in 401 this semester.

**Before Wednesday, October 8**-
Please read pages 149-159. You may skip the subsection on
*Comparing Rates*.

**Before Monday, October 13**-
Please read pages 159-169. Try to understand the reason for using the
Tukey or Tukey-Kramer procedure. Don't worry about the details of
carrying it out (e.g., ignore the stuff about tables and q-values). We will
learn how to get Tukey and Tukey-Kramer confidence intervals and
adjusted p-values using SAS. I won't expect you to know Scheffe's
procedure or about any of the procedures described in the
*Others*subsection.

**Before Wednesday, October 15**-
Please read the handout that we will discuss in class on Wednesday.

**Before Wednesday, October 22**-
Please read pages 174 to the middle of 182. The case studies are more complex than I would like, so do not be concerned about understanding everything about the case studies. Focus more on the concept of linear regression and the least-squares regression line.

**Before Monday, October 27**-
Please read pages 182 through 196. Don't worry about the "computer centering trick" discussed on the bottom of page 187 and the top of 188. Also you will not be asked any questions about Section 7.4.4 on calibration.

**Before Wednesday, November 5**-
Please read all of Chapter 8 including the Conceptual Exercises. Note that your text reverses the X and Y axes of normal probability plots relative to the way SAS makes normal probability plots.

**Before Friday, November 7**-
Please read pages 235 to 243.

**Before Monday, November 10**-
Please read Section 9.3. Do your best to understand indicator variables and interaction terms. These are important concepts.

**Before Wednesday, November 12**-
Please read pages 250 to 260. We will not cover this material in class. Conceptual Exercises 10 and 11 are good ones to read and understand.

**Before Friday, November 21**-
Please read Chapter 10. You may ignore the formulas in Section 10.4.3. We have learned how to get SAS to compute standard errors of linear combinations of regression coefficients. You may skip Section 10.4.5.

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