Use the regression equation to predict the value of y for x = -Xy-5 - 3411 6 - 6A. 7.921B. - 0.995C. -4.765O D. -6.4051- 1- 13- 2 04 12- 43-5-3.8. Assume that the variables x and y have a significant correlation.- 48

We have given two variables x and y, we have to predict the value of y for x.Given observation and…

Answered: Use the regression equation to predict…

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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A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: уах+ b a = -1.098 b = 37.154 r2 = 0.444889 r = -0.667 Use this to predict the number of situps a person who watches 11 hours of TV can do. situps = [one decimal accuracy]
The correlation for the data is r=1 and a=0.05 should regression analysis be done Find the equation of the regression line y = a+bx A= B= Find y when x=40
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 58 inches. Is the result close to the actual weight of 572 pounds? Use a significance level of 0.05. Chest size (inches) 46 57 53 41 40 40 Weight (pounds) 384 580 542 358 306 320 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=nothing+nothingx (Round to one decimal place as needed.)
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.091 b=30.228 r2=0.698896 r=-0.836 Use this to predict the number of situps a person who watches 3.5 hours of TV can do (to one decimal place)
Find the equation of the regression line for given data
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day () and number of sit ups a person can do (y). The results of the regression were: y=ax+b a3D-0.838 b=28.783 es 72-0.784996 r=-0.886 rences borations Use this to predict the number of sit ups a person who watches 1 hours of TV can do, and please round your answer to a whole number. gle Drive ce 365 Submit Question adent Course aluations ere to search Chp ins prt sc delete f12 f9 f10 fa f5 f6 +1 f4 backspa & $4 8. 6 3 O E R T II 5
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (xx) and number of sit ups a person can do (yy). The results of the regression were: y=ax+b a=-1.013 b=27.906 r2=0.498436 r=-0.706 Use this to predict the number of sit ups a person who watches 12 hours of TV can do, and please round your answer to a whole number.
. Determine the regression equation using values you create for x and y for at least 10 pairs of data. Show the regression equation, correlation coefficient, and coefficient of determination. Then switch the x and y values for each data point. Based on that, again show the regression equation, correlation coefficient, and coefficient of determination. Discuss the similarities and differences between the results.
How can the coefficient of determination be interpreted?
Find the equation of the regression line for the given data. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. What is the regression equation? Predict the value of y for x=503. (Please show me how you figured this out) Predict the value of y for x=641.
Find the equation of the least-squares regression line ŷ and the linear correlation coefficient r for the given data. Round the constants, a, b, and r, to the nearest hundredth. {(1, 4.3), (2, 6.4), (4, 7.8), (6, 11.7), (8, 16.4)}
The mall has a set of data with employee age (X) and the corresponding number of annual on-the-job-accidents(Y). Analysis on the set finds that the regression equation is Y=100-3X. What is the likely number of accidents for someone aged 30? 97 100 10 none of the above

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Use the regression equation to predict the value of y for x = -3.8. Assume that the variables x and y have a significant correlation. X-5 -3 4 y 11 6-6 OA. 7.921 a OB. -0.995 OC. -4.765 OD. -6.405 1 - 1 3 - 1 -2 0 2 4 1 -4 -5 8 3-4