Candidate Heights Media periodically discuss the issue of heights of winning presidential candidates and heights of their main opponents. The accompanying table lists the heights (cm) from several recent presidential elections. 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 = 0.05. Click the icon to view the heights of the candidates. President 174 180 191 179 180 182 195 184 179 186 191 184 181 189 Opponent 180 183 183 177 181 178 178 180 178 180 172 190 181 171 200 Construct a scatterplot. Choose the correct graph below. O A. 160+ 160 200 President Height (cm) Q B. 200 160- 160 President Height (cm) 200 The linear correlation coefficientis r = (Round to three decimal places as needed.) Determine the null and alternative hypotheses. Ho: P H₁: P (Type integers or decimals. Do not round.) The test statistic is t=0. (Round to two decimal places as needed.) C... The P-value is (Round to three decimal places as needed.) 200- 160- 160 200 President Height (cm) ▶ 200- OA. Yes, because presidential candidates are nominated for reasons other than height. OB. Yes, because height is the main reason presidential candidates are nominated. OC. No, because height is the main reason presidential candidates are nominated. O D. No, because presidential candidates are nominated for reasons other than height. 160+ 160 200 President Height (cm) Because the P-value of the linear correlation coefficient is the significance level, there sufficient evidence to support the claim that there is a linear correlation between the heights of winning presidential candiates and the heights of their opponents. Should we expect that there would be a correlation?
Candidate Heights Media periodically discuss the issue of heights of winning presidential candidates and heights of their main opponents. The accompanying table lists the heights (cm) from several recent presidential elections. 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 = 0.05. Click the icon to view the heights of the candidates. President 174 180 191 179 180 182 195 184 179 186 191 184 181 189 Opponent 180 183 183 177 181 178 178 180 178 180 172 190 181 171 200 Construct a scatterplot. Choose the correct graph below. O A. 160+ 160 200 President Height (cm) Q B. 200 160- 160 President Height (cm) 200 The linear correlation coefficientis r = (Round to three decimal places as needed.) Determine the null and alternative hypotheses. Ho: P H₁: P (Type integers or decimals. Do not round.) The test statistic is t=0. (Round to two decimal places as needed.) C... The P-value is (Round to three decimal places as needed.) 200- 160- 160 200 President Height (cm) ▶ 200- OA. Yes, because presidential candidates are nominated for reasons other than height. OB. Yes, because height is the main reason presidential candidates are nominated. OC. No, because height is the main reason presidential candidates are nominated. O D. No, because presidential candidates are nominated for reasons other than height. 160+ 160 200 President Height (cm) Because the P-value of the linear correlation coefficient is the significance level, there sufficient evidence to support the claim that there is a linear correlation between the heights of winning presidential candiates and the heights of their opponents. Should we expect that there would be a correlation?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:Candidate Heights
Media periodically discuss the issue of heights of winning presidential candidates and heights of their main opponents.
The accompanying table lists the heights (cm) from several recent presidential elections. 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 = 0.05.
Click the icon to view the heights of the candidates.
Construct a scatterplot. Choose the correct graph below.
O A.
O B.
Opponent Height (cm)
President 174 180 191 179 180 182 195 184 179 186 191 184 181 189
Opponent 180 183 183 177 181 178 178 180 178 180 172 190 181 171
200-
160-
160
200
President Height (cm)
ON
Opponent Height (cm)
200
160+
160
200
President Height (cm)
The linear correlation coefficientis r =
(Round to three decimal places as needed.)
Determine the null and alternative hypotheses.
Ho: P
H₁: P
(Type integers or decimals. Do not round.)
The test statistic is t=.
(Round to two decimal places as needed.)
The P-value is
(Round to three decimal places as needed.)
Opponent Height (cm)
C.
200-
160+
160
200
President Height (cm)
O
O
O
Opponent Height (cm)
D.
OA. Yes, because presidential candidates are nominated for reasons other than height.
B. Yes, because height is the main reason presidential candidates are nominated.
OC. No, because height is the main reason presidential candidates are nominated.
O D. No, because presidential candidates are nominated for reasons other than height.
200
I
160+
200
160
President Height (cm)
Because the P-value of the linear correlation coefficient is
the significance level, there
sufficient evidence to support the claim that there is a linear correlation between the heights of winning
presidential candiates and the heights of their opponents.
Should we expect that there would be a correlation?
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