Why do we do the one-factor ANOVA instead of just doing a bunch of t tests? When doing many non-independent tests, our assumptions used to calculate p values fail. When doing many non-independent tests, our assumptions used to calculate alpha values f When doing many tests, the type II errors adds up and this allows us to keep this low. When doing many non-independent tests, our assumptions used to calculate t values fail. When doing many tests, the type I errors adds up and this allows us to keep this low.

Q: 54 22

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A:

Q: Suppose that X, Y, and Z are jointly distributed random variables, that is, they are defined on the…

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A: Given,             369343*9+124*5

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A:

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A:

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Q: 74.1 6.

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Q: 2. 7. 58

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Q: 869-789

A: SOLUTION-