isted below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars. Construct a catterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to onclude that there is a linear correlation between court incomes and justice salaries? Based on the results, does it appear that justices ight profit by levying larger fines? Court Income Justice Salary 64.0 404.0 1567.0 1130.0 271.0 254.0 112.0 154.0 30.0 D 31 44 91 58 47 61 26 27 19 onstruct a scatterplot. Choose the correct graph below. DA. O B. OC. D. AJustice Salary 100- AJustice Salary 100- AJustice Salary 100- AJustice Salary 100+ 50- 50- 50- 50- 0+ 0- 0- 0. 800 1600 800 1600 800 1600 800 1600 Court Income Court Income Court Income Court Income The linear correlation coefficient is r = Round to three decimal places as needed.) The test statistic is t = Round to three decimal places as needed.) The P-value is Round to three decimal places as needed.) Because the P-value is V than the significance level 0.05, there V sufficient evidence to support the claim that there is a inear correlation between court incomes and justice salaries for a significance level of a = 0.05. Based on the results, does it appear that justices might profit by levying larger fines? O A. It appears that justices profit the same despite the amount of the fines. O B. It does not appear that justices might profit by levying larger fines. O C. It does appear that justices might profit by levying larger fines. O D. It does appear that justices might profit by issuing smaller fines.

2. Consider the following examples; would you expect the correlation coefficient to be close to 1, -1, or 0 (10 points):   The amount of time a dog is walked, and the number of hours the dog sleeps at night     Outdoor temperature and snowfall.         The length of time someone wears braces and their SAT scores.         3. The following graph represents the amount of time that someone studies for their final exam, and their final examination grade (HINT) (20 points).       Student 1 Student 2 Student 3 Student 4 Student 5 Student 6 Hours Studied 4 7 11 8 10 8 Final Exam Grade 55% 72% 88% 93% 91% 84%     Graph the following students as ordered pairs. Let the x-axis represent the hours studied, and the y-axis represent the students’ final exam grade.                         Circle the value that best represents the estimate of r: (circle one)   -0.99, -0.62, -0.30, 0, 0.30, 0.75, 0.85, 0.99

An economist wants to determine whether there is a linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. The data are shown in the table below. c. Compute and interpret the correlation coefficient. d. Compute and interpret the coefficient of determination. e. Test for the significance of the linear relationship. Use a 0.05 level of significance. State your conclusion. Hint: Your conclusion is either of the following. • There is a significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. • There is no significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. GDP 1.6 3.6 4.9 1.1 0.9 2.9 2.7 2.3 1.6 1.5 (trillion dollars) Carbon Dioxide Emissions 428.2 828.8 1214.2 444.6 264 415.3 571.8 454.9 358.7 573.5 (millions of metric tons)

find linear correlation coefficient, P value, and test statistic.