Listed below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between court incomes and justice salaries? Based on the results, does it appear that justices might profit by levying larger fines? Court Income 65.0 | 403.0|1568.0|1132.0 271.0| 252.0|112.0| 150.0| 34.0 |e Justice Salary 31| 42 | 91 57 | 46 60 24 25 17 What are the null and alternative hypotheses? B. Hg: p=0 O A. Ho: p=0 H:p>0 OC. Ho: p=0 O D. Ho: p#0 H,:p=0 H,:p<0 Construct a scatterplot. Choose the correct graph below. OA. O B. Oc. OD. AJustice Salary 100- AJustice Salary 100- AJustice Salary 100- AJustice Salary 100- Q 50- 50- ...-- 50- 50- 0- 0- 0++ 0++ 1600 800 Court Income 800 1600 Court Income 800 1600 800 1600 Court Income Court Income

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Please explain each step clearly, and no excel formula should be used for solving this problem

Listed below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a= 0.05. Is there sufficient evidence to conclude that there is a linear correlation between court incomes and justice salaries? Based on the results, does it appear that justices might profit by levying larger fines? Court Income Justice Salary 65.0 406.0 1566.0 1131.0 274.0 253.0 110.0 152.0 31.0 e 29 45 94 58 46 61 25 26 19 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.) V than the significance level 0.05, there court incomes and justice salaries for a significance level of a = 0.05. Because the P-value is V sufficient evidence to support the claim that there is a linear correlation between Based…

After gathering data about the number of starfish and measuring the pollution in areas of the ocean you find a negative linear correlation between pollution levels and number of starfish. What can you conclude based on this information? a. There is a confounding variable that is affecting both pollution and starfish. b. As pollution rises the number of starfish falls c. That pollution is causing starfish to die, leading to the negative correlation d. That pollution is supporting starfish, leading to the negative correlation

Listed below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between court incomes and justice salaries? Based on the results, does it appear that justices might profit by levying larger fines? Court Income 65.0 406.0 1567.0 1131.0 271.0 254.0 111.0 152.0 30.0 Justice Salary 29 45 91 58 45 60 24 25 19 What are the null and alternative hypotheses? O A. Ho: p#0 O B. Ho: p=0 H₁: p=0 H₁: p0 H₁: p=0 Construct a scatterplot. Choose the correct graph below. A. B. C. ★Justice Salary AJustice Salary 100- Justice Salary D. 100- ★Justice Salary 100+ ▬▬▬▬▬▬ · ■● 50- 50- 50+ 0- 0- 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…

Use the output below to test to see if there is a significant positive linear relation between height and head circumference in children. Use a 5% level of significance. Correlations: Height, Head Circ Pearson correlation of Height and Head Circ 0.911 P-Value 0.000

Assume that you have paired values consisting of heights (in inches) and weights (in lb) from 40 randomly selected men. The linear correlation coefficient r is 0.506. Find the value of the coefficient of determination. What practical information does the coefficient of determination provide? Choose the correct answer below. O A. The coefficient of determination is 0.256. 25.6% of the variation is explained by the linear correlation, and 74.4% is explained by other factors. O B. The coefficient of determination is 0.744. 25.6% of the variation is explained by the linear correlation, and 74.4% is explained by other factors. O C. The coefficient of determination is 0.744. 74.4% of the variation is explained by the linear correlation, and 25.6% is explained by other factors. O D. The coefficient of determination is 0.256. 74.4% of the variation is explained by the linear correlation, and 25.6% is explained by other factors.