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Suppose the Federal Aviation Administration (FAA) would like to compare the on-time performances of different airlines...

Suppose the Federal Aviation Administration (FAA) would like to compare the on-time performances of different airlines on domestic, nonstop flights. To determine if Airline and Status are dependent, what are the appropriate hypotheses?

A)HO: Airline and Status are independent of each other.
HA: Airline and Status display a positive correlation.

B)Two of the other options are both correct.

C)HO: Airline and Status are independent of each other.
HA: Airline and Status are dependent on one another.

D)HO: Airline and Status are not related to each other.
HA: Airline and Status display a negative correlation.

E)HO: Airline and Status are related to one another.
HA: Airline and Status are independent of one another.

2.A political poll asked potential voters if they felt the economy was going to get worse, stay the same, or get better during the next 12 months. The party affiliations of the respondents were also noted. To determine if Party Affiliation and Response are dependent, what are the appropriate hypotheses?

A)There is not enough information to choose the correct set of hypotheses.

B)HO: Party Affiliation and Response are not related to one another.
HA: Party Affiliation and Response display a negative correlation.

C)HO: Party Affiliation and Response are independent of each other.
HA: Party Affiliation and Response display a positive correlation.

D)HO: Party Affiliation and Response are not related to each other.
HA: Party Affiliation and Response are dependent on each other.

E)HO: Party Affiliation and Response are associated with one another.
HA: Party Affiliation and Response are not related to each other

3. Consider the first and second exam scores of the 10 students listed below. Calculate the Pearson's correlation coefficient for the dataset below and interpret what that means.

exam 1 exam 2
24 37
22 35
21 42
22 40
21 41
23 37
23 30
23 37
21 48
25 30

A)The correlation is -0.774 . There is a strong negative linear association between Exam 1 and Exam 2

B) The correlation is -0.774 . There is a weak negative linear association between Exam 1 and Exam 2 .

C)The correlation is 0.774 . There is a strong positive linear association between Exam 1 and Exam 2 .

D)The correlation is -0.774 . There is a strong positive linear association between Exam 1 and Exam 2 .

E)The correlation is 0.774 . There is a strong negative linear association between Exam 1 and Exam 2 .

4. Consider the first and second exam scores of the 10 students listed below. Calculate the Pearson's correlation coefficient for the dataset below and interpret what that means.

exam 1 exam 2
23 29
29 24
19 19
17 27
24 22
10 20
29 28
20 18
25 18
16

29

A)The correlation is 0.147 . There is a weak negative linear association between Exam 1 and Exam 2 .

B)The correlation is -0.147 . There is a weak positive linear association between Exam 1 and Exam 2

C)The correlation is 0.147 . There is a strong positive linear association between Exam 1 and Exam 2

D)The correlation is -0.147 . There is a weak negative linear association between Exam 1 and Exam 2

E)

The correlation is 0.147 . There is a weak positive linear association between Exam 1 and Exam 2 .

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