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. O C. O D 200 200 200 Opponent Height (cm) Opponent Height (cm) Opponent Height (cm) Opponent Height (cm) 160 1604 160- 160 160 200 160 200 160 200 160 200 President Height (cm) President Height (cm) President Height (cm) 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 VO (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.) 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? O A. No, because height is the main reason presidential candidates are nominated. O B. No, because presidential candidates are nominated for reasons other than height. O C. Yes, because height is the main reason presidential candidates are nominated. O D. Yes, because presidential candidates are nominated for reasons other than height.