Please note that the steps show rounded numbers, but that the final answers to the problems are calculated without rounding.
| Problem | Part | Solution |
|---|---|---|
| 1 | - | |
| 2 | - | \(n_1 \times \hat{p}_1 \geq 10 \text{ and } n_1 \times (1 - \hat{p}_1) \geq 10\) \(261\times(0.038) = 10 \geq 10 \text{ and } 261\times(1 - 0.038) = 251\geq 10\) \(n_2 \times \hat{p}_2 \geq 10 \text{ and } n_2 \times (1 - \hat{p}_2) \geq 10\) \(1614\times(0.103) = 166 \geq 10 \text{ and } 1614\times(1 - 0.103) = 1448\geq 10\) The requirements are met. |
| 3 | - | ( -0.092 , -0.037 ) We are 95 % confident that the true difference of the proportions of city children with hay fever and rural children with hay fever is between -0.092 and -0.037 . If you swapped the definition of groups 1 and 2, then you would get the same values with opposite signs: ( 0.037 , 0.092 ). This is also correct. |
| 4 | - | No. This means that it is plausible that the likelihood of a child contracting hay fever is different in the city than in rural areas. |
| 5 | - | \(n_1 \times \hat{p}_1 \geq 10 \text{ and } n_1 \times (1 - \hat{p}_1) \geq 10\) \(200,000\times(0.0002) = 33 \geq 10 \text{ and } 200,000\times(1 - 0.0002) = 199,967\geq 10\) \(n_2 \times \hat{p}_2 \geq 10 \text{ and } n_2 \times (1 - \hat{p}_2) \geq 10\) \(200,000\times(0.0006) = 115 \geq 10 \text{ and } 200,000\times(1 - 0.0006) = 199,885\geq 10\) The requirements are met. |
| 6 | - | ( -0.00053 , -0.00029 ) We are 95 % confident that the true difference of the proportions of vaccinated children who developed polio and non-vaccinated children who developed polio is -0.00053 and -0.00029 . If you swapped the definition of groups 1 and 2, then you would get the same values with opposite signs: ( 0.00029 , 0.00053 ). This is also correct. |
| 7 | - | |
| 8 | - | \(n_1 \times \hat{p}_1 \geq 10 \text{ and } n_1 \times (1 - \hat{p}_1) \geq 10\) \(117\times(0.624) = 73 \geq 10 \text{ and } 117\times(1 - 0.624) = 44\geq 10\) \(n_2 \times \hat{p}_2 \geq 10 \text{ and } n_2 \times (1 - \hat{p}_2) \geq 10\) \(168\times(0.518) = 87 \geq 10 \text{ and } 168\times(1 - 0.518) = 81\geq 10\) The requirements are met. |
| 9 | - | \(H_0: p_1 = p_2\) \(H_a: p_1 > p_2\) |
| 10 | - | \(\hat{p_1} = 0.624\) \(\hat{p_2} = 0.518\) |
| 11 | - | \(z = 1.775\) |
| 12 | - | \(\text{p-value} = 0.038\) |
| 13 | - | |
| 14 | - | reject the null hypothesis |
| 15 | - | There is sufficient evidence to suggest that the proportion of men who cheat in college is greater than the proportion of women who cheat in college. |
| 16 | - | The p-value would double and be equal to 0.076 . This p-value is not significant and we would fail to reject the null hypothesis. With a two sided test we would not have sufficient evidence to conclude that there is a difference between the proportion of women and men who cheat in college. |
| 17 | - | \(n_1 \times \hat{p}_1 \geq 10 \text{ and } n_1 \times (1 - \hat{p}_1) \geq 10\) \(1655\times(0.03) = 50 \geq 10 \text{ and } 1655\times(1 - 0.03) = 1605\geq 10\) \(n_2 \times \hat{p}_2 \geq 10 \text{ and } n_2 \times (1 - \hat{p}_2) \geq 10\) \(1652\times(0.019) = 31 \geq 10 \text{ and } 1652\times(1 - 0.019) = 1621\geq 10\) The requirements are met. |
| 18 | - | \(H_0: p_1 = p_2\) \(H_a: p_1 \neq p_2\) |
| 19 | - | \(\hat{p_1} = 0.03\) \(\hat{p_2} = 0.019\) |
| 20 | - | \(z = 2.129\) |
| 21 | - | \(\text{p-value} = 0.033\) |
| 22 | - | |
| 23 | - | reject the null hypothesis |
| 24 | - | There is sufficient evidence to suggestthat the proportion of Clarinex subjects with dry mouth is different than the proportion of placebo subjects with dry mouth. |