Calculate the Spearman correlation coefficient between two sets of data: set A = [6, 8, 10, 12, 14] and set B = [2, 4, 6, 8, 10].
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Q: Listed below are annual data for various years. The data are weights (metric tons) of imported…
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Q: Listed below are annual data for various years. The data are weights (metric tons) of imported…
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- In baseball, is there a linear correlation between batting average and home run percentage? Let x represent the batting average of a professional baseball player, and let y represent the player's home run percentage (number of home runs per 100 times at bat). A random sample of n = 7 professional baseball players gave the following information.The table list chest sizes and weights of anesthetized bears. Chest (in). 49 35 41 41 63 57 Weight (Ib) 348 166 320 262 390 290 Compute the correlation coefficient, r.The following table shows the weekly sales, test scores & achievement ratings of 5 salespersons working for a local car dealership: Salesperson Weekly Sales (Y) Sales Aptitude Test Score (x1) Mechanical Achievement (x2) Walters 11 10 6 Sullivan 5 4 2 Obmer 8 1 4 Smith 12 7 5 Jones 4 3 1 Brown 6 5 3 Black 7 2 2 Calculate the multiple correlation coefficient.. Select one: a. 0.925 b. 0.952 c. 0.295 d. 0.592
- Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. 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 lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? Lemon Imports Crash Fatality Rate 229 266 359 480 530 15.9 15.6 15.5 15.3 14.9 Construct a scatterplot. Choose the correct graph below. OA. В. Ос. D. Ay 17- Ay 17- Ay 17- Ay 17- 16- 16- 16- 16- 15- 15- 15- 15- 14+ 14+ 14- 14+ 200 400 600 200 400 600 200 400 600 200 400 600 The linear correlation coefficient r is (Round to three decimal places as needed.)Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. 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 lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? Lemon Imports Crash Fatality Rate 231 266 359 480 532 15.9 15.7 15.4 15.2 14.8 Ay 17- Ay 17- Ay 17+ Ay 17- 16- 16- 16- 16- 15- 15- 15- 15- X 14- 14+ 14- 14- 200 400 600 200 400 600 200 400 600 200 400 600 The linear correlation coefficient r is (Round to three decimal places as needed.) The P-value is (Round to three decimal places as needed.) Because the P-value is than the significance level 0.05, there sufficient evidence to support the claim that there is a linear correlation between lemon imports and crash fatality rates for a…Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. 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 lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? Lemon Imports Crash Fatality Rate 228 264 358 482 531 15.9 15.7 15.5 15.3 14.9
- Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. 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 lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? Lemon Imports Crash Fatality Rate 266 15.7 228 358 484 531 15.8 15.5 15.2 14.8 What are the null and alternative hypotheses? O B. Ho: p=0 O A. Ho: p#0 H1:p=0 H1:p0 H,: p#0 Construct a scatterplot. Choose the correct graph below. OA. B. Oc. OD. Ay 17- Ay 17- AY 17- Ay 17- 16- Q 16- 16- 16- 15- 15- 15- 15- 14- 14+ 14- 14- 200 400 600 200 400 600 200 400 6ỏ0 200 400 600 The linear correlation coefficient is r= (Round to three decimal places as needed.)Compute r, the correlation coefficient, rounded to two decimal places, for the following paired data set: Data Set 1: 4, 3, 4, 4 Data Set 2: 3, 1, 2, 1 If needed, please round your answer to two decimal places.The table below includes data from taxi rides. The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars. Is there sufficient evidence to conclude that there is a linear correlation between the time of the ride and the tip amount? 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. Use a significance level of a = 0.01. Does it appear that riders base their tips on the time of the ride? Click here for information on the taxi rides. Construct a scatterplot. Choose the correct graph below. O A. Tip Amount ($) 25- Q 0 35 G Ride time (minutes) Determine the linear correlation coefficient. The linear correlation coefficient is r= (Round to three decimal places as needed.) Tip Amount ($) B. 25- 0- 0 35 G Ride time (minutes) Taxi data ip Amount (S C. 25- 0- 35 Ride time…
- The following table shows the annual family income of the students enrolled in the JRMSU-TC and their general weighted average (GPA). Students Annual Family Income (Pesos) General weighted average (GPA) % 1 85 100,000 50,000 2 79 3 150,000 4 180,000 5 300,000 6 500,000 7 230,000 2. Determine the correlation coefficient. 82 85 93 92 95Calculate the Spearman's rank correlation coefficient between the following two sets of data: X = [3, 5, 4, 7, 6] Y = [2, 4, 3, 8, 7]A nutritionist collects data from 25 popular breakfast cereals. For each cereal, the number of calories per serving is plotted on the x-axis against the number of milligrams of sodium on the y-axis. The value of r for the resulting scatterplot is 0.83. How would the value of the correlation coefficient, r, change if sodium was plotted on the x-axis and calories plotted on the y-axis? The value of r would increase. The value of r would not change. The value of r would change to –0.83. The value of r could increase or decrease, depending of the strength of the new relationship.
