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**Before Wednesday, January 14**- Please read Sections 1.1-1.6 and 1.8. Section 1.8 mentions
*normal theory tests*. These tests include the*t*-tests and*F*-tests that we learned about in 401.

**Before Friday, January 16**- Please read Sections 1.9 and 1.10.

**Before Wednesday, January 21**- Please read Sections 2.1 through 2.8. You are not required to follow the calculus discussion on top of page 48. You do not need to show that the cross-product term sums to zero at the bottom of page 52. Neither of these concepts is difficult if you have the appropriate background, but that background is not a prerequisite for the course.

**Before Friday, January 23**- Please read Sections 2.9 through 2.14. The SAS program
power.sas will do calculations like those discussed in Section 2.14, so don't worry about using the tables discussed in Section 2.14.

**Before Wednesday, January 28**- Please read Sections 3.1 and 3.2.

**Before Friday, January 30**- Please read Section 3.3. You do not need to know any of the formulas or tables discussed in this reading assignment. I will show you how to use SAS to do the analyses discussed in the text. (orthopoly.sas is a SAS program that does the analyses described in this reading assignment.)

**Before Wednesday, February 4**- Please read sections 3.4-3.9, skipping the material on Scheffe's Test and the Sudent-Newman-Keuls multiple-range test. Don't worry about any of the details, formulas, or tables used in these sections. Just try to understand the basic problems being considered. We will learn how to do these analyses in SAS. Read the handout Adjustments for Multiple Testing and Estimation carefully. This contains the information that I think is most useful. The program filter.sas contains examples that show how to make all comparisons between pairs of means using Tukey's method and code for comparing all treatments to a control using Dunnett's method.

**Before Wednesday, February 18**- Please read pages 123 to 128. See crab.sas for SAS code that will produce residual plots and normal probability plots. We won't cover the rest of Chapter 4.

**Before Friday, February 20**Please read pages 175 to 190 in Chapter 6. Also read and answer the questions on the handout Two-Factor ANOVA.

**Before Friday, February 27**- Read pages 190 to 199. You may ignore Tables 6.9 and 6.12 and the descriptions of the calculations used to compute the tables. See sludge.sas for an analysis of the data described in Example 6.3. See uptake.sas for an analysis of the data described in Example 6.4.

**Before Wednesday, March 4**- Please read Section 6.6 and 6.7 carefully. Don't worry about the computational details in Section 6.7. The SAS program hearing.sas computes the sum of squares for nonadditivity for Example 6.6. (The calculations done by SAS are more precise than the book's calculations. The text does too much rounding at intermediate steps.) Also read Section 6.9 up through the top of page of page 214. The rest of the Section 6.9 deals with computation of sums of squares. You are not expected to read that material. We will use SAS's Type III sums of squares for tests about interaction and main effects when working with unbalanced data from factorial experiments.

**Before Monday, March 9**- Please read Sections 5.1 through 5.7.

**Before Monday, March 29**- Please read Section 5.9.

**Before Friday, April 2**- Please read Sections 8.1 and 8.2.

**Before Monday, April 5**- Read pages 275 to the top of 278. Read 281 to the top half of 284. Read Section 8.4. You can use SAS to randomly assign experimental units to treatments in a Latin square design. See rlatinsq.sas
which can be used to assign experimental units to treatments for the example problem that we will discuss in class.

**Before Monday, April 12**- Please read all of Chapter 14. This chapter discusses split-plot designs which are among the most common designs used at ISU. Split-plot designs are often mistakenly analyzed as completely randomized two-factor experiments.

**Before Wednesday, April 21**- Please read the handout containing some notes on mixed models. Also read the handout on the analysis of split-split-plot experiments.

**Before Friday, April 23**-
Please read pages 492 to 498. Also read the first subsection of Section 15.4 and the handout on repeated measures analysis.

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