The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Should we expect that there would be a correlation? Use a significance level of a= 0.01. E Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. O A. OB. OC. OD. Q Q 70 70 70- 70 70 Best Actress (years) 20 20 20 70 20 Best Actress (years) 70 Best Actress (years) Best Actress (years) The linear correlation coefficient is r= -0.170 (Round to three decimal places as needed.) Determine the null and alternative hypotheses. Ho P =0 H,: P + 0 (Type integers or decimals. Do not round.) The test statistic is t=-0.54 (Round to two decimal places as needed.) The P-value is 0.597 (Round to three decimal places as needed.) Because the P-value of the linear correlation coefficient is v the significance level, there v suficient evidence to support the claim that there is a linear correlation between the ages of Best Actresses and Best Actors. Should we expect that there would be a correlation? O A. No, because Best Actors and Best Actresses are not typically the same age. O B. No, because Best Actors and Best Actresses typically appear in different movies, so we should not expect the ages to be correlated. OC. Yes, because Best Actors and Best Actresses typically appear in the same movies, so we should expect the ages to be correlated. O D. Yes, because Best Actors and Best Actresses are typically the same age.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
icon
Related questions
Question

I need help to complete the last 2 parts please. 

First part which is Completing the sentence which says 

Because the​ P-value of the linear correlation coefficient is (Less or equal / Greater than) the significance​ level, there ( Is / Is not) sufficient evidence to support the claim that there is a linear correlation between the ages of Best Actresses and Best Actors.

Seccond part : Multiple choises at the end 

Thanks in advance.

The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. Construct a scatterplot, find the value of the linear correlation
coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Should
would be a correlation? Use a significance level of a = 0.01.
expect that there
E Click the icon to view the ages of the award winners.
Construct a scatterplot. Choose the correct graph below.
O A.
OB.
OC.
OD.
70
Best Actress (years)
Best Actress (years)
Best Actress (years)
Best Actress (years)
The linear correlation coefficient is r=-0.170
(Round to three decimal places as needed.)
Determine the null and alternative hypotheses.
Ho: P = 0
H, P
(Type integers or decimals. Do not round.)
The test statistic is t=-0.54
(Round to two decimal places as needed.)
The P-value is 0.597
(Round to three decimal places as needed.)
Because the P-value of the linear correlation coefficient is
v the significance level, there
V sufficient evidence to support the claim that there is a linear
correlation between the ages of Best Actresses and Best Actors.
Should we expect that there would be a correlation?
O A. No, because Best Actors and Best Actresses are not typically the same age.
O B. No, because Best Actors and Best Actresses typically appear in different movies, so we should not expect the ages to be correlated.
O C. Yes, because Best Actors and Best Actresses typically appear in the same movies, so we should expect the ages to be correlated.
O D. Yes, because Best Actors and Best Actresses are typically the same age.
est Actor (ye ars)
Transcribed Image Text:The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Should would be a correlation? Use a significance level of a = 0.01. expect that there E Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. O A. OB. OC. OD. 70 Best Actress (years) Best Actress (years) Best Actress (years) Best Actress (years) The linear correlation coefficient is r=-0.170 (Round to three decimal places as needed.) Determine the null and alternative hypotheses. Ho: P = 0 H, P (Type integers or decimals. Do not round.) The test statistic is t=-0.54 (Round to two decimal places as needed.) The P-value is 0.597 (Round to three decimal places as needed.) Because the P-value of the linear correlation coefficient is v the significance level, there V sufficient evidence to support the claim that there is a linear correlation between the ages of Best Actresses and Best Actors. Should we expect that there would be a correlation? O A. No, because Best Actors and Best Actresses are not typically the same age. O B. No, because Best Actors and Best Actresses typically appear in different movies, so we should not expect the ages to be correlated. O C. Yes, because Best Actors and Best Actresses typically appear in the same movies, so we should expect the ages to be correlated. O D. Yes, because Best Actors and Best Actresses are typically the same age. est Actor (ye ars)
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 2 steps

Blurred answer
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman