The following data represent the calories and sugar, in grams, of various breakfast cereals.ProductCaloriesa. Compute the covariance.Sugar7.72303003.0(Round to three decimal places as needed.)40027.123,921.719.6470b. Compute the coefficient of correlation.49050057021.4(Round to three decimal places as needed.)Use the data above to complete parts (a) through (d).c. Which do you think is more valuable in expressing the relationship between calories andsugar-the covariance or the coefficient of correlation? Explain.O A. The covariance is more valuable. It is an exact measure of the strength of a linearrelationship.O B. The covariance is more valuable. It is not susceptible to the negative effects of lurkingvariables.OC. The correlation is more valuable. It can be used to determine the relative strength of alinear relationship.O D. The correlation is more valuable. It is the better measure for positive relationships.d. What conclusions can you reach about the relationship between calories and sugar?View instructor tipO Time Remaining: 00:58:45Next608 PM76°FO Type here to search2/17/2022ert144esc%23$47@23.Y.R Ttab

Answered: Image /qna-images/answer/8e1ec135-3939-43af-9cf1-a44347b8c977.jpg

Answered: The following data represent the…

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 asking prices (in Rands) and the actual selling prices (in Rands), after bargaining, of 8commodities are given below.Commodity A B C D E F G HAsking price, x 150 350 400 750 100 650 600 250Selling price, y 120 200 400 550 80 450 350 200Find the correlation coefficient for the above data.A. 0.8224B. 0.3722C. 0.9438D. 0.5318
Use a computer or statistical calculator to calculate the correlation coefficient in parts a through c below. Cost Miles a. The table shows the approximate distance between selected cities and the approximate cost of flights between those cities. Calculate the correlation coefficient between cost and miles. 190 958 413 3095 r= (Round to three decimal places as needed.) 256 1998 90 429 436 3008 b. This table shows the same information, except that the distance was converted to kilometers by multiplying the numbers of miles by 1.609 and rounding to the nearest kilometer. What happens to the correlation coefficient when numbers are multiplied by a positive constant? Cost Kilometers O 190 1541 413 4980 (Round to three decimal places as needed.) 256 3215 90 690 436 4840 A. The correlation is The correlation coefficient remains the same when the numbers are multiplied by a positive constant. B. The correlation is The correlation coefficient increases when the numbers are multiplied by a…
A population data set produced the following information. N = 250. Ex = 9870, E y = 1452, E xy = 84,890 E = 485,590, and E = 135,115. Find the linear correlation coefficient p. Round your answer to three decimal places. p = i
The following show the respective ages in years and the corresponding weighs in lbs of 8 women. What is the coefficient of Correlation? Age (x) Weight (y) 42 120 38 135 45 140 27 115 16 98 25 123 37 130 38 132 Select one: a. 0.847 b. 0.478 c. .748 d. .447
Match each scatterplot shown below with one of the four specified correlations. O O O O O O 8 0% O O 00 00 O Do O O O 8 8 O O 00 o o O 00 a O O O a. 0.31 b. -0.26 c. 0.87 d. -0.82
A study of emergency service facilities investigated the relationship between the number of facilities and the average distance traveled to provide the emergency service. The following table gives the data collected. Average Distance Number of Facilities (miles) 1.67 11 1.11 16 0.82 21 0.62 27 0.50 30 0.47 (a) Develop a scatter diagram for these data, treating average distance traveled as the dependent variable. 1.8 T 35 1.8 1.8 1.6- 1.6- 1.6 30 1.4 1.4 1.4 1.2 25 1.2 1.2 1. 1. 1. 20 0.8 0.8 0.8 0.6 15 0.6 0.6- 0.4 0.4 0.4 10 0.2 0.2 0.2 0. 5 0. 0. 10 15 20 25 30 35 0. 0.2 0.4 0.6 0.8 1. 1.2 1.4 1.6 1.8 5 10 15 20 25 30 35 10 15 20 25 30 35 Number Distance Number Number (b) Does a simple linear regression model appear to be appropriate? Explain. O Yes, the scatter diagram suggests that there is a linear relationship. O No, the scatter diagram suggests that there is a curvilinear relationship. O No, the scatter diagram suggests that there is no relationship. (c) Develop an estimated…
Match each scatterplot shown below with one of the four specified correlations. O O ∞oo O oooº 0000 8 9088 08 8 a. -0.89 b. -0.12 c. 0.55 d. 0.98
Table #10.1.6 contains the value of the house and the amount of rental income in a year that the house brings in ("Capital and rental," 2013). Find the correlation coefficient of determination and then interpret both Table #10.1.6: Data of House Value versus Rental Value Rental Value Rental Value Rental Rental Value 67500 81000 6656 77000 4576 75000 7280 6864 95000 7904 94000 8736 90000 6240 85000 7072 121000 12064 115000 7904 110000 7072 104000 7904 135000 8320 130000 9776 126000 6240 125000 7904 145000 8320 140000 9152 7488 9568 140000 135000 7488 165000 13312 165000 8528 155000 148000 8320 178000 11856 174000 10400 170000 9568 170000 12688 匯 190000 200000 225000 8320 12272 8528 200000 200000 10608 194000 11232 8320 10400 11648 10192 12272 10400 200000 240000 214000 208000 240000 10192 240000 12064 12480 244500 11232 12896 12480 289000 11648 270000 262000 325000 12480 310000 303000 300000 12480
The asking prices (in Rands) and the actual selling prices (in Rands), after bargaining, of 8 commodities are given below. Commodity A D E F G H Asking price, x 150 350 400 750 100 650 600 250 Selling price, y 120 200 400 550 80 450 350 200 Find the correlation coefficient for the above data. A. 0.8224 B. 0.3722 С. 0.9438 D. 0.5318 Activate
The following are the age (in years) and price (in hundreds of dollars) data for a certain type of car. A scatterplot of the data is given to the right. 500- 400 0 300 80 80 Age (x) Price (y) 270 255 276 408 369 291 340 311 404 309 6. 6. 1 4 4 5 1 200 0 2 4 6 8 10 a. Obtain the linear correlation coefficient. b. Interpret the value of r in terms of the linear relationship between the two variables. c. Discuss the graphical interpretation of the value of r. d. Obtain the value of the coefficient of determination by squaring r. a. r= 3|(Round to three decimal places as needed)
Calculate co-efficient of correlation from the following data : 500 1000 1500 2000 X: Y: 2500 3000 3500 100 200 300 400 500 600 700
Find the Pearson product-moment correlation coefficient of the data set shown below:Where the car price is Y and car age is the X. Car Age (in years) Price in dollars 4 6300 4 5800 5 5700 5 4500 7 4500 7 4200 8 4100 9 3100 10 2100 11 2500 12 2200

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