Question

(17.31) Young men in North America and Europe (but not in Asia) tend to think they...

(17.31) Young men in North America and Europe (but not in Asia) tend to think they need more muscle to be attractive.
One study presented 200 young American men with 100 images of men with various levels of muscle.
Researchers measure level of muscle in kilograms per square meter (kg/m2) of fat-free body mass.
Typical young men have about 20 kg/m2.
Each subject chose two images, one that represented his own level of body muscle and one that he thought represented what women prefer.
The mean gap between self-image and what women prefer was 2.35 kg/m2.
Suppose that the muscle gap in the population of all young men has a Normal distribution with standard deviation 2.5 kg/m2.
If young men thought that their own level of muscle was about what women prefer, the mean muscle gap in the study described in Exercise 16.20 (above) would be 0.
We suspect (before seeing the data) that young men think women prefer more muscle than they themselves have.

A. What is the value of the test statistic z?
Give your answer to 2 decimal places.
Fill in the blank:

B. You can tell just from the value of z that the evidence in favor of the alternative is very strong (that is, the P-value is very small).
Explain why this is true.

  1. Because large values of the statistic show that the data is consistent with the null hypothesis.
  2. Because large values of the statistic show that the data is not consistent with the null hypothesis.
  3. Because large values of the statistic show that the observed result would be likely to occur if the alternative hypothesis were true.
  4. Because large values of the statistic show that the observed result would be unlikely to occur if the null hypothesis were true.

Enter the number(s) of the choice(s) you wish to select. Separate multiple selections with commas or semicolons.

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Answer #1

Let denotes the true average gap between self-image and what women prefer.

ans-> ii) Because large values of the statistic show that the data is not consistent with the null hypothesis.

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