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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. Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. OA. 70- 20- 20 70 Best Actress (years) G The linear correlation coefficient is r= (Round to three decimal places as needed.) B. 20- 20 70 Best Actress (years) Q C O C. 70- Best Actress 28 30 29 61 33 Best Actor 41 37 36 43 49 20- Best Actresses and Best Actors 20 70 Best Actress (years) 32 50 Q G 46 29 60 23 40 56 64 53 43 43 32 57 D O D. - X 70- 20+ 20 70 Best Actress (years) Q

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. Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. OA. 70- 20- 20 70 Best Actress (years) G The linear correlation coefficient is r= (Round to three decimal places as needed.) B. 20- 20 70 Best Actress (years) Q C O C. 70- Best Actress 28 30 29 61 33 Best Actor 41 37 36 43 49 20- Best Actresses and Best Actors 20 70 Best Actress (years) 32 50 Q G 46 29 60 23 40 56 64 53 43 43 32 57 D O D. - X 70- 20+ 20 70 Best Actress (years) Q

MATLAB: An Introduction with Applications
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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The image shows a statistical analysis task involving the ages of acting award winners. It includes the following components: **Task Summary:** - The task involves constructing a scatterplot with the ages of best actress and best actor award winners. The goal is to find the linear correlation coefficient \( r \) and the P-value \( p \) to determine if there is significant evidence of a linear correlation between the ages of best actress and best actor winners. A significance level of \( \alpha = 0.01 \) is used. **Scatterplot Choices:** - Four scatterplot options (A, B, C, D) are presented. Each scatterplot represents different data point distributions of the ages of best actress winners (x-axis) versus best actor winners (y-axis). **Scatterplot Interpretation:** - Each scatterplot graph measures ages in years, ranging from 20 to 70 years for both actresses and actors. - The correct scatterplot choice is marked as "B." **Data Table:** - The ages data for both categories are presented in a table: - Best Actress Ages: 28, 30, 29, 61, 33, 32, 46, 29, 60, 23, 43, 57 - Best Actor Ages: 41, 37, 36, 43, 49, 64, 50, 54, 43, 50, 56, 43, 32 **Linear Correlation Coefficient:** - An input box is provided to calculate the linear correlation coefficient \( r \). - The coefficient \( r \) should be rounded to three decimal places. This exercise is useful for understanding how to use scatterplots to analyze correlations in paired data and evaluate statistical evidence through correlation coefficients and significance tests.
Transcribed Image Text:The image shows a statistical analysis task involving the ages of acting award winners. It includes the following components: **Task Summary:** - The task involves constructing a scatterplot with the ages of best actress and best actor award winners. The goal is to find the linear correlation coefficient \( r \) and the P-value \( p \) to determine if there is significant evidence of a linear correlation between the ages of best actress and best actor winners. A significance level of \( \alpha = 0.01 \) is used. **Scatterplot Choices:** - Four scatterplot options (A, B, C, D) are presented. Each scatterplot represents different data point distributions of the ages of best actress winners (x-axis) versus best actor winners (y-axis). **Scatterplot Interpretation:** - Each scatterplot graph measures ages in years, ranging from 20 to 70 years for both actresses and actors. - The correct scatterplot choice is marked as "B." **Data Table:** - The ages data for both categories are presented in a table: - Best Actress Ages: 28, 30, 29, 61, 33, 32, 46, 29, 60, 23, 43, 57 - Best Actor Ages: 41, 37, 36, 43, 49, 64, 50, 54, 43, 50, 56, 43, 32 **Linear Correlation Coefficient:** - An input box is provided to calculate the linear correlation coefficient \( r \). - The coefficient \( r \) should be rounded to three decimal places. This exercise is useful for understanding how to use scatterplots to analyze correlations in paired data and evaluate statistical evidence through correlation coefficients and significance tests.
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