Consider two populations of coins, one of pennies and one of quarters. A random sample of 25 pennies was selected, and the mean
age of the sample was 32 years. A random sample of 35 quarters was taken, and the mean age of the sample was 19 years. For the sampling distribution of the difference in sample means, have the conditions for normality been met?
(A) Yes, the conditions for normality have been met because the distributions of age for the two populations are approximately normal.
(B) Yes, the conditions for normality have been met because the sample sizes taken from both populations are large enough.
(C) No, the conditions for normality have not been met because neither sample size is large enough and no information is given about the distributions of the populations.
(D) No, the conditions for normality have not been met because the sample size for the pennies is not large enough and no information is given about the distributions of the populations.
(E) No, the conditions for normality have not been met because the sample size for the quarters is not large enough and no information is given about the distributions of the populations.
No, the conditions for normality have not been met because the sample size for the quarters is not large enough and no information is given about the distributions of the populations.
Step-by-step explanation:
"The Kolmogorov-Smirnov test (K-S) and Shapiro-Wilk (S-W) test are designed to test normality by comparing your data to a normal distribution with the same mean and standard deviation of your sample. If the test is NOT significant, then the data are normal, so any value above .05 indicates normality"
