|a.||Plot the complementary form of the factorial graph of Figure 5.2. Which do you consider more useful?|
|b.||Plot the complementary form of the factorial graph in the left panel of Figure 5.4. Which way do you consider more useful?|
|c.||Do the same as in (b) for the center panel of Figure 5.4.|
|d.||Compare both forms of the two-way, AB data table of Figure 5.5.|
|a.||Centration on Damage.|
|b.||Centration on Intent.|
|c.||Blame = Intent + Damage.|
|d.||Blame = Intent × Damage.|
|e.||Accident-configural integration: Blame independent of amount of damage if damage is accidental; otherwise, Blame = Intent + Damage.|
|f.||* Centration on the larger of Intent and Damage.|
|a.||Relying on visual inspection, guess which sources in the Anova will be substantial, which will not.|
|b.||What features of your graph are clues to the variability of the data?|
|c.||What can Anova add to this visual inspection?|
4. In the left panel of Figure 5.4, the two levels of A have quite different effects. Yet the text says “The null hypothesis for A is true in this case.” What's going on?
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Publication information: Book title: Empirical Direction in Design and Analysis. Contributors: Norman H. Anderson - Author. Publisher: Lawrence Erlbaum Associates. Place of publication: Mahwah, NJ. Publication year: 2001. Page number: 151.
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