Suppose r12 = 0.50 r13 = 0.60 r23 =0.80. If one wants to get the association between variables 1 and 2 while holding constant the effect of variable 3, thenhe will get a correlation coefficient value equal toO a. 0.04O b. 0.88O c. 0.08O d. 0.96

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Answered: Suppose r12 = 0.50 r13 = 0.60 r23…

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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#2 and #3
Which of the following correlation coefficient would reflect a conclusion made by a researcher that two variables are not related? r = –.30 r = +.02 r = +.36 r = –.98
runs 8.17. Compute Karl Pearson's coefficient of correlation between X and Y from the following observairons. X: 1 3 4. Y: 1 4 9. 16 Is the correlation coefficient equal to unity ? If not, why not ?
Below is data for two variables, X and Y. Answer the questions that follow. X Y X-MX Y-MY (X-MX)2 (Y-MY)2 (X-MX)(Y-MY) 3 3 -2 -1 4 1 2 4 3 -1 -1 1 1 ___ 6 4 1 ___ 1 0 0 7 6 2 2 ___ 4 4 Positive or negative correlation?
The following statement contains an error. Choose the statement that best explains the error. "The correlation between shoe size and height is 0.87 inches" A. Correlation requires that both of the variables be categorical B. When stating the correlation coefficient, one must state whether it is a positive or negative relationship C. This statement does not tell us whether or not shoe size is correlated with height D. When reporting correlation, one does not report units because correlation has no units E. There is no error in this statement
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
A random sample of college students was surveyed about how they spend their time each week. The scatterplot below displays the relationship between the number of hours each student typically works per week at a part- or full-time job and the number of hours of television each student typically watches per week. The correlation between these variables is r = –0.63, and the equation we would use to predict hours spent watching TV based on hours spent working is as follows: Predicted hours spent watching TV = 17.21 – 0.23(hours spent working) Since we are using hours spent working to help us predict hours spent watching TV, we’d call hours spent working a(n) __________________ variable and hours spent watching TV a(n) __________________ variable. The correlation coefficient, along with what we see in the scatterplot, tells us that the relationship between the variables has a direction that is _________________ and a strength that is ______________________. According to the…
Suppose a friend of yours computes a correlation coefficient of +1.10 and comes to you for advice as to how to interpret it. What would you tell your friend?
The correlation coefficient between the variables x and y is r=0.78 . If Sigma x=1.56, Sigma y=2.00, x bar=12,y bar=22 Find the equations of the registration lines Y on X
The following table shows the number of units of a certain item sold by a store over a month in terms of the price in dollars charged by the store. Price in dollars 0.90 1.00 1.15 1.25 1.40 Number sold . 315 280 230 215 195 Use technology to find the correlation coefficient for the data. (Use decimal notation. Give your answer to two decimal places.) correlation coefficien What type of correlation is there between the price and the number sold?
This is a continuation of the last question I posted: f. The value of linear correlation coefficient r is i. 0.948 ii. 0.974 iii. -0.948 iv. -0.974 g.Based on your answer in part (f), the linear dependance between weekly exercise time and change in cholesterol level is strong negative i. True ii. False H. When weekly exercise time is 460 minutes (approximately 66 minutes per day), the 95 percent confidence interval for change in cholesterol level is (197.3, 225.4). This means that: i. If one person exercises 460 minutes per week, his/hers change in cholesterol level will be between 197.3 and 225.4 with 95 percent certainty.ii. If several people exercise 460 minutes per week, their average change in choles- terol level will be between 197.3 and 225.4 with 95 percent certainty. I. When weekly exercise time is 460 minutes (approximately 66 minutes per day), the 95 percent prediction interval for change in cholesterol level is (155.1, 267.6). This means that i. If one person…
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Suppose r12 = 0.50 r13 = 0.60 r23 =0.80. If one wants to get the association between variables 1 and 2 while holding constant the effect of variable 3, then he will get a correlation coefficient value equal to O a. 0.04 O b. 0.88 O c. 0.08 O d. 0.96