SOLUTION The proportion of Y responses in this sample is 24 = 0.75 32 Using the population proportion of 0.6 (given earlier), the standard deviation for the distri- bution of sample proportions is p(1-p) 0.6 (1 0.6) 0.09 %3D 32 The sample statistic, p = 0.75, therefore has a standard score of %3D sample proportion – population proportion 0.75 0.6 = 1.67 = 2 standard deviation 0.09

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What is the sample mean and proportion of this problem?
mean? What is the probability of selecting another sample with a proportion greater than the
one you selected?
SOLUTION The proportion of Y responses in this sample is
24
0.75
%3D
32
Using the population proportion of 0.6 (given earlier), the standard deviation for the distri-
bution of sample proportions is
P(1 p)
0.6 (1 0.6)
= 0.09
|3D
32
The sample statistic, p = 0.75, therefore has a standard score of
sample proportion – population proportion
0.75 0.6
= 1.67
= 2
standard deviation
0.09
The sample proportion is 1.67 standard deviations above the mean of the distribution. Using
Table A-1, we find that a standard score of 1.67 corresponds to the 95.25th percentile. The
probability of selecting another sample with a proportion less than the one we selected is about
0.9525, and the probability of selecting another sample with a proportion greater than the one
we selected is about 0.0475. In other words, if we were to select 100 random samples of 32
responses, we should expect to see only about 5 samples with a higher proportion than for the
sample we selected.
Transcribed Image Text:mean? What is the probability of selecting another sample with a proportion greater than the one you selected? SOLUTION The proportion of Y responses in this sample is 24 0.75 %3D 32 Using the population proportion of 0.6 (given earlier), the standard deviation for the distri- bution of sample proportions is P(1 p) 0.6 (1 0.6) = 0.09 |3D 32 The sample statistic, p = 0.75, therefore has a standard score of sample proportion – population proportion 0.75 0.6 = 1.67 = 2 standard deviation 0.09 The sample proportion is 1.67 standard deviations above the mean of the distribution. Using Table A-1, we find that a standard score of 1.67 corresponds to the 95.25th percentile. The probability of selecting another sample with a proportion less than the one we selected is about 0.9525, and the probability of selecting another sample with a proportion greater than the one we selected is about 0.0475. In other words, if we were to select 100 random samples of 32 responses, we should expect to see only about 5 samples with a higher proportion than for the sample we selected.
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