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Lastly, Bryant and colleagues (2005) predicted that vividness of recall of positive memories would be associated with higher levels of happiness. Although their analysis was

Lastly, Bryant and colleagues (2005) predicted that vividness of recall of positive memories would be associated with higher levels of happiness.

Although their analysis was a bit more complicated than we are prepared for, they basically used multiple regression to examine the associations between condition (beta = 0.30, p <.05, one-tailed) and vividness of recall (beta = 0.63, p <.0001, one-tailed) as predictors of happiness.

Question 31 of 392 Points

Which variable (condition or vividness of recall) was the stronger predictor of happiness?

  • A.

Condition

  • B.

Vividness of recall

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Question 32 of 392 Points

For the previous question: How do you know?

  • A.

Thepvalue for conditionwas smaller

  • B.

The betavalue for controlwas larger

  • C.

The betavalue for vividness of recall was larger

  • D.

Thepvalue for vividness of recall was smaller

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Question 33 of 393 Points

For a one unit increase in vividness of imagery, how much does happiness go up?

  • A.

No way to tell (we need more information)

  • B.

0.30

  • C.

0.63

  • D.

0.001

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Question 34 of 392 Points

What is one major limitation of the analysis described above?

  • A.

The researchers ran a multiple regression with a categorical outcome (happiness), thereby violating the assumptions of the test

  • B.

The researchers used a one-tailed test when two-tailed tests are preferred (might be missing an opposite effect)

  • C.

None. This is the most perfect analysis I have ever seen

  • D.

We do not know if either predictor is significant, leaving us wondering whether either variable significantly predicts happiness

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Question 35 of 392 Points

Why is multiple regression preferable to single regression?

  • A.

It allows you to control for the effects of other predictors

  • B.

It allows you to examine the interaction between multiple predictors and an outcome

  • C.

It allows you to examine effects on multiple dependent variables

  • D.

It allows you to ignore the effect of other predictors

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