10.1

9.

Right-tailed, μ

10.

Left-tailed, p

11.

Two-tailed, σ

12.

Right-tailed, p

13.

Left-tailed, μ

14.

Two-tailed, σ

15.

Ho: p=0.399

H1: p>0.399

Making a Type I error would mean that the proportion of students who enroll and earn a degree within six years is greater than 0.399, while in fact the proportion of students is not greter than 0.399

Making a Type II error would mean that the proportion of students who enroll and earn a degree within six years is not greater than 0.399, while in fact the proportion of students is greater than 0.399

17.

Ho: μ=245,700

H1: μ<245,700

Making a Type I error would mean that the existing home prices in the neighborhood are lower than 245,700, while in fact the existing home prices are not lower than 245,700

Making a Type II error would mean that the existing home prices in the neighborhood are not lower than 245,700, while in fact the existing home prices are lower than 245,700

19.

Ho: σ=0.7 psi

H1: σ<0.7 psi

Making a Type I error would mean that the pressure variability has been reduced below 0.7 psi, while in fact the pressure variability has not been reduced below 0.7 psi

Making a Type II error would mena that the pressure variability has not been redeuced below 0.7 psi, while in fact the variability has been reduced below 0.7 psi

21.

Ho: μ=48.79

H1: μ≠48.79

Making a Type I error would mean that the mean monthly revenue per cell phone is not 48.79, while in fact the mean revenue is 48.79

Making a Type II error would mean that the mean monthly revenue per cell phone is 48.79, while in fact the mean revenue is not 48.79

10.2

7. p=75/200=0.375 a) z0=0.375-0.3/√0.3 (1-0.3)/200=2.31 b) P(z>2.31)=0.0104 c) Because the test statistic is greater than the critical value, and the p value is less than the level of significance, so reject the hypothesis

9. p=78/150=0.52 a) z0=0.52-0.55/√0.55 (1-0.55)/150=-0.74 b) P(z<-0.74)=0.230 c) Because test statistic is greater than critical value, and p-value is greater than the level of significance, so do not reject the hypothesis

11. p=440/500=0.88 a) z0=0.88-0.9/√0.9 (1-0.9)/500=-1.49 b) 2P(Z<-1.49)=0.136 c) Because the test statistic is an outlier of the critical region, and the p-value is greater than the level of significance, so do not reject the hypothesis

13.

The p-value 0.2743 means that if the hypothesis is true, the expected result would be in about 27 or 28 out of 100 samples, which is unusual.And because the p-value is large, so do not reject the hypothesis.

15. Note this is slightly modified version of the book problem Just answer a) b) and c) fromt the skeleton.

  1. 320/678=0.472

Ho: p=0.5

H1: p<0.5

  1. z0=0.472-0.5/√0.5 (1-0.5)/678=-1.45, P(z<-1.45)=0.0735, because 0.0735>0.05, so do not reject the hypothesis but it doesn’t prove that the predictions are correct

17.

  1. p=19/863=0.022, z0=0.022-0.019/√0.019 (1-0.019)/863=0.65, critical value: z0.01=2.33

  2. Because 0.65<2.33, so do not reject the hypothesis but it’s not able to prove more than 1.9% of Lipitor users experience flulike symptoms as a side effect

19.

  1. p=51/105=0.486, z0=0.486-0.36/√0.36 (1-0.36)/105=2.69, critical value: z0.05=1.645

  2. Because 2.69>1.645, so reject the hypothesis and prove that Hawaii has a higher proportion of traffic fatalities involving a positive BAC than the United States as a whole