MATH 110 Module 7 Exam/ MATH110
Introduction to Statistics: Portage Learning
Module 7 Exam
Exam Page 1
a) Define the null and alternative hypothesis for the following. Also, explain what it would mean to
make a Type I error and explain what it would mean to make a Type II error.
The newspaper in a certain city had a circulation of 19,000 per day in 2010. You believe that the
newspaper’s circulation is different than 19,000 today.
Ho: u = 19000
H1: u ≠ 19000
Type I Error: Reject the null hypothesis saying the mean newspaper circulation in a certain city is
19000 per day when the mean IS 19000 per day.
Type II Error: Accept the null hypothesis saying the mean newspaper circulation in a certain city is
19000 per day when the mean it IS DIFFERENT than 19000 per day.
b) Define the null and alternative hypothesis for the following. Also, explain what it would mean to
make a Type I error and explain what it would mean to make a Type II error.
A certain website had 6000 hits per month a year ago. You believe that the number of hits per month
is less than that today.
Ho: u = 6000
H1: u < 6000
Type I Error: Reject the null hypothesis saying a certain website had mean number of 6000 hits per
month a year ago when the mean number of hit DID have 6000 hits per month.
Type II Error: Accept the null hypothesis saying a certain website had a mean number of 6000 hits
per month a year ago when the mean number of hit was LESS THAN 6000 hits per month.
Answer Key
, a) Define the null and alternative hypothesis for the following. Also, explain what it would mean to
make a Type I error and explain what it would mean to make a Type II error.
The newspaper in a certain city had a circulation of 19,000 per day in 2010. You believe that the
newspaper’s circulation is different than 19,000 today.
a) H0: μ=19,000.
H1:μ≠19,000.
Type I error: Reject the null hypothesis that the circulation today is 19,000 when the circulation today
actually is 19,000.
Type II error: Do not reject the null hypothesis when the circulation is different than 19,000.
b) Define the null and alternative hypothesis for the following. Also, explain what it would mean to
make a Type I error and explain what it would mean to make a Type II error.
A certain website had 6000 hits per month a year ago. You believe that the number of hits per month
is less than that today.
b) H0: μ=6000.
H1:μ<6000.
Type I error: Reject the null hypothesis that the website gets 6000 hits per month when the website
gets at least 6000 hits per month.
Type II error: Do not reject the null hypothesis when the number of hits per month is less than 6000.
Introduction to Statistics: Portage Learning
Module 7 Exam
Exam Page 1
a) Define the null and alternative hypothesis for the following. Also, explain what it would mean to
make a Type I error and explain what it would mean to make a Type II error.
The newspaper in a certain city had a circulation of 19,000 per day in 2010. You believe that the
newspaper’s circulation is different than 19,000 today.
Ho: u = 19000
H1: u ≠ 19000
Type I Error: Reject the null hypothesis saying the mean newspaper circulation in a certain city is
19000 per day when the mean IS 19000 per day.
Type II Error: Accept the null hypothesis saying the mean newspaper circulation in a certain city is
19000 per day when the mean it IS DIFFERENT than 19000 per day.
b) Define the null and alternative hypothesis for the following. Also, explain what it would mean to
make a Type I error and explain what it would mean to make a Type II error.
A certain website had 6000 hits per month a year ago. You believe that the number of hits per month
is less than that today.
Ho: u = 6000
H1: u < 6000
Type I Error: Reject the null hypothesis saying a certain website had mean number of 6000 hits per
month a year ago when the mean number of hit DID have 6000 hits per month.
Type II Error: Accept the null hypothesis saying a certain website had a mean number of 6000 hits
per month a year ago when the mean number of hit was LESS THAN 6000 hits per month.
Answer Key
, a) Define the null and alternative hypothesis for the following. Also, explain what it would mean to
make a Type I error and explain what it would mean to make a Type II error.
The newspaper in a certain city had a circulation of 19,000 per day in 2010. You believe that the
newspaper’s circulation is different than 19,000 today.
a) H0: μ=19,000.
H1:μ≠19,000.
Type I error: Reject the null hypothesis that the circulation today is 19,000 when the circulation today
actually is 19,000.
Type II error: Do not reject the null hypothesis when the circulation is different than 19,000.
b) Define the null and alternative hypothesis for the following. Also, explain what it would mean to
make a Type I error and explain what it would mean to make a Type II error.
A certain website had 6000 hits per month a year ago. You believe that the number of hits per month
is less than that today.
b) H0: μ=6000.
H1:μ<6000.
Type I error: Reject the null hypothesis that the website gets 6000 hits per month when the website
gets at least 6000 hits per month.
Type II error: Do not reject the null hypothesis when the number of hits per month is less than 6000.
