10.1

9.

It is a right-tailed test and the parameter is the population mean.

10.

It is a left-tailed test and the parameter is p which is population proportion.

11.

It is a two-tailed test and the parameter is sigma which is the population standard deviation.

12.

It is a right-tailed test and the parameter is population proportion.

13.

It is a left-tail test and the parameter is a population mean.

14.

This is a two-tail test and the parameter is sigma, which is the population standard deviation.

15.

Ho: p= 0.399

H1: p > 0.399

Making a type one error would mean that the proportion is greater than 0.399, but in fact it is not.

Making a type two error would mean the opposite- the proportion is not greater than 0.399 when in fact it is.

17.

Ho: pop. mean = $245,700

H1: pop. mean < $245,700

Making a type 1 error would mean that current prices are lower than $245,700 when they are not actually lower at the moment.

Making a type 2 error would mean the opposite-that the current prices are not lower than this pop. mean when in reality they are.

19.

Ho: pop. standard deviation = 0.7

H1: pop. standard deviation < 0.7

Making a type 1 error would mean that the psi is lower than 0.7 but really the psi is not below 0.7

Making a type 2 error would mean the opposite- the psi is not below 0.7 but actually it is.

21.

Ho: pop. mean = $48.79

H1: pop. mean ≠ $48.79

Making a type 1 error would mean that the monthly revenue is not $48.79 when it really is.

Making a type 2 error is the opposite- the monthly revenue is $48.79 when it really isn’t.

10.2

7.

  1. ~2.3
  2. ~0.01
  3. Using the classical approach, we reject the null hypothesis, and using the p-value approach, we also reject the null hypothesis.

9.

  1. ~ -0.74
  2. ~ 0.23
  3. We don’t reject the null hypothesis.

11.

  1. ~ -1.49
  2. ~ 0.136
  3. We don’t reject the null hypothesis.

13.

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. Test stat: - 1.45– We do not reject the null hypothesis.

17.

  1. p-value= 0.258

  2. We don’t reject the null hypothesis.

19.

  1. p-value= 0.0036

  2. In this case we reject the null hypothesis.