10.1

9.

Right tail test. The parameter being tested is the population mean.

10.

Left tail test. The parameter being tested is the population proportion.

11

Two-tail test. The parameter being tested is the population standard deviation.

12

Right tail test. The parameter being tested is the population proportion.

13

Left tail test. The parameter being tested is the population mean.

14

Two-tail test. The parameter being tested is the population standard deviation.

15

H0: p= 10.5

H1: p> 10.5

  1. A type I error would mean that the statistician rejected that H0 is equal to 10.5 but it’s actually true.

  2. A type II error would mean that the the statistician did not reject that the null hypothesis is equal to 10.5 but it’s actually greater than 10.5.

17

H0: mu = 218600

H1: mu < 218600

  1. A type I error would mean that the statistician rejected that H0 is equal to 218600 when it actually is equal to 218600.

  2. A type II error would mean that the statistician did not reject that the mean price is equal to 218600 but it’s actually less than 218600.

19

H0: sigma=0.7

H1: sigma <0.7

  1. A type I error would mean that the statistician rejected that H0 is equal to 0.7 when in reality it is.

  2. A type II error would mean that the statistician did not reject that H0 is equal to 0.7 when in reality it is less than 0.7.

21

H0: mu= 47.47

H1: mu≠ 47.47

  1. A type I error would mean that the statistician rejected that H0 is equal to 47.47 when in reality it is equal to 47.47

  2. A type II error would mean that the statistician did not reject that H0 is equal to 47.47 when in reality it isn’t equal to 47.47.

10.2

7

np(1-9) is greater than or equal to 10.

The Pvalue = .0104

Reject the Null Hypothesis.

9

np (1-.52) is greater than or equal to 10.

Pvalue= .2266

Do not reject the null hypothesis.

11

np(1-.88) is greater than or equal to 10.

Pvalue= .8106

Do not reject the null hypothesis.

13

This p value is the number that needs to be compared with the alpha value in order to determine whether or not the null hypothesis should be rejected.

15

pvalue= .2578

There is not enough evidence to conclude that more than 1.9% of users experience flu-like symptoms.

17

pvalue= .1379

There is not enough evidence to conclude that a majority of adults believe this.

19

pvalue= .0047

There is enough evidence to support that adults believe this.