chapter 7

There were 5,317 previously owned homes sold in a western city in the year 2000. The distribution of the sales prices of these homes was strongly right-skewed, with a mean of $206,274 and a standard deviation of $37,881. If all possible simple random samples of size 100 are drawn from this population and the mean is computed for each of these samples, which of the following describes the sampling distribution of the sample mean?

• (A) Approximately normal with mean $206,274 and standard deviation $3,788

• (B) Approximately normal with mean $206,274 and standard deviation $37,881

• (C) Approximately normal with mean $206,274 and standard deviation $520

• (D) Strongly right-skewed with mean $206,274 and standard deviation $3,788

• (E) Strongly right-skewed with mean $206,274 and standard deviation $37,881

For a sample of 42 rabbits, the mean weight is 5 pounds and the standard deviation of weights is 3 pounds. Which of the following is most likely true about the weights for the rabbits in this sample?

• (A) The distribution of weights is approximately normal because the sample size is 42, and therefore the central
  limit theorem applies

• (B) The distribution of weights is approximately normal because the standard deviation is less than the mean.

• (C) The distribution of weights is skewed to the right because the least possible weight is within 2 standard
  deviations of the mean.

• (D) The distribution of weights is skewed to the left because the least possible weight is within 2 standard
  deviations of the mean.

• (E) The distribution of weights has a median that is greater than the mean.

• (A) highly skewed with mean 10 and standard deviation 10

• (B) highly skewed with mean 10 and standard deviation 5

• (C) highly skewed with mean 10 and standard deviation 0.5

• (D) approximately normal with mean 10 and standard deviation 10

• (E) approximately normal with mean 10 and standard deviation 0.5

• (C) Yes, because the wording of the question is not biased.

Which of the following pairs of sample size n and population proportion p would produce the greatest standard deviation for the sampling distribution of a sample proportion

• (A) n = 1,000 and p close to 0

• (B) n = 1,000 and p close to 1

• (C) n = 1,000 and p close to 1/2

• (D) n = 100 and p close to 0

• (E) n = 100 and p close to 1/2