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AP Statistics 7.9 Carrying Out a Test for the Difference of Two Population Means- MCQs - Exam Style Questions

Question

A study about robins, a type of bird, was conducted to compare the mean number of eggs laid by robins in metal nest boxes to the mean number of eggs laid by robins in wood nest boxes. The results of the study are summarized in the table.
Summary Statistics for Each Type of Nest
 Metal Nest BoxesWood Nest Boxes
Sample Size6045
Mean Number of Eggs4.964.61
Standard Deviation of Number of Eggs1.010.89
Let \(\mu_M\) represent the mean number of eggs laid by robins in metal nest boxes for robins similar to those in the study. Let \(\mu_W\) represent the mean number of eggs laid by robins in wood nest boxes for robins similar to those in the study. A two-sample \(t\)-test for a difference of population means was conducted for the hypotheses \(H_0:\mu_M=\mu_W\) versus \(H_a:\mu_M\ne\mu_W\).
Assume the conditions for inference have been met. At the 10 percent level of significance, which of the following can be concluded?
(A) The \(p\)-value is less than \(0.10\), and \(H_0\) should be rejected.
(B) The \(p\)-value is less than \(0.10\), and \(H_0\) should not be rejected.
(C) The \(p\)-value is greater than \(0.10\), and \(H_0\) should be rejected.
(D) The \(p\)-value is greater than \(0.10\), and \(H_0\) should not be rejected.
(E) The \(p\)-value cannot be determined from the given information.
▶️ Answer/Explanation
Compute the test statistic for a two-sample Welch \(t\)-test:
\[ t=\frac{\bar x_M-\bar x_W}{\sqrt{\frac{s_M^2}{n_M}+\frac{s_W^2}{n_W}}} =\frac{4.96-4.61}{\sqrt{\frac{1.01^2}{60}+\frac{0.89^2}{45}}}. \]
\(\frac{1.01^2}{60}=0.01700,\;\frac{0.89^2}{45}=0.01760\Rightarrow\) SE \(=\sqrt{0.03460}\approx0.1860\).
\(t=\dfrac{0.35}{0.1860}\approx1.88.\)
Welch degrees of freedom (approx.):
\[ \nu\approx \frac{\left(\frac{s_M^2}{n_M}+\frac{s_W^2}{n_W}\right)^2} {\frac{\left(\frac{s_M^2}{n_M}\right)^2}{n_M-1}+\frac{\left(\frac{s_W^2}{n_W}\right)^2}{n_W-1}} \approx 100. \]
Two-sided \(p\)-value for \(t\approx1.88\) with \(\nu\approx100\) is \(p\approx0.06\text{–}0.07\).
Since \(p<0.10\), we reject \(H_0\) at the 10% level.
Answer: (A) The \(p\)-value is less than \(0.10\), and \(H_0\) should be rejected.

Question

To investigate whether vegetarians have lower cholesterol levels, on average, than non-vegetarians, a nutritionist obtained independent random samples of cholesterol levels for the two groups. The data are summarized below.
 VegetariansNon-vegetarians
Mean\(198\)\(207\)
Standard Deviation\(32\)\(41\)
n\(62\)\(231\)
Based on the data, which of the following statements is true?
(A) At the \(5\%\) significance level, vegetarians have a significantly lower mean cholesterol level than non-vegetarians do.
(B) At the \(1\%\) significance level, vegetarians have a significantly lower mean cholesterol level than non-vegetarians do.
(C) At the \(5\%\) significance level, vegetarians have a significantly higher mean cholesterol level than non-vegetarians do.
(D) At the \(1\%\) significance level, vegetarians have a significantly higher mean cholesterol level than non-vegetarians do.
(E) At the \(10\%\) significance level, there is no significant difference in cholesterol levels between vegetarians and non-vegetarians.
▶️ Answer/Explanation
Detailed solution

1. Define Hypotheses:
– \(H_0: \mu_V = \mu_{NV}\) (Mean cholesterol levels are the same).
– \(H_a: \mu_V < \mu_{NV}\) (Vegetarians have a lower mean cholesterol level).

2. Calculate the Test Statistic:
Use a two-sample t-test for the difference of means.
\(t = \frac{(\bar{x}_V – \bar{x}_{NV}) – 0}{\sqrt{\frac{s_V^2}{n_V} + \frac{s_{NV}^2}{n_{NV}}}} = \frac{198 – 207}{\sqrt{\frac{32^2}{62} + \frac{41^2}{231}}} \approx \frac{-9}{4.878} \approx -1.845\)

3. Find the P-value:
Using the conservative degrees of freedom, \(df = \min(61, 230) = 61\).
The p-value is the area to the left of the t-statistic for a one-tailed test: \(P(t_{df=61} < -1.845) \approx 0.035\).

4. Make a Conclusion:
The p-value (\(0.035\)) is less than \(0.05\) but greater than \(0.01\). Therefore, there is a statistically significant difference at the \(5\%\) level, but not at the \(1\%\) level.
Answer: (A)

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