Arnold fits a linear model to the data using the statistical software, R. A summary of that model fit is given below:CoefficientsEstimateStd Errort value Pr( > [t])(Intercept)2.1947.8380.280.781Wingspan1.2220.0949712.8693.55е-17Residual standard error: 2.319 on 48 degrees of freedomMultiple R-squared: 0.7753, Adjusted R-squared: 0.77061. Use the computer output to write the estimated linear regression equation for predicting Standing Reach from Wingspan.ŷ =+2. Which of the following is the correlation coefficient for the linear relationship between Standing Reach and Wingspan?OA. 0.7753В. -0.8805C. -0.7753D. 0.88053. Each additional 1 inch of Wingspan is associated with a(n) increasev ofinches in Standing Reach.4. What is the expected Standing Reach if a player has a Wingspan of 0 inches?5. The wingspan of Al-Farouq Aminu is 87.25 inches. Calculate the estimated value for the standing reach of Al-Farouq Aminu that is predicted by thelinear model.Estimated value = 6. Al-Farouq Aminu's standing reach is measured as 108.5 inches. Use this information and your result from part 5 to calculate the residual for thisplayer.Residual =7. What are the null and alternative hypotheses to test if there is a linear relationship between Standing Reach and Wingspan?А. Но : bi %3D 0 vs. HA : bi # 0В. Но : Ві 3 0 vs. HA : Bi +0OC. Ho : B1 = bị vs. HA : B1 + bịD. Ho : B1 = 0 vs. HA : B1 > 08. Based on the computer output, what is the test statistic for the test in part 7?Test statistic:9. Based on the computer output, the results of the hypothesis test tell us that we have extremely strong v evidence that there isalinear relationship between Standing Reach and Wingspan.10. Use information from the computer output to calculate a 99% confidence interval for the slope, B1, of the regression line predicting StandingReach from Wingspan.IMPORTANT! You MUST use a t* value rounded to EXACTLY 3 decimal places in this calculation. Round your final answers to 4 decimal places.

The response variable is Y = Standing Reach and the explanatory variable is X = Wingspan. Note :…

Answered: Use the computer output to write 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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Interpret the intercept and the coefficients of D1 and D2 in the regression above.
A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam scores (y). The results of the regression were: y=ax+b a=5.865 b=25.06 r²=0.81 r=0.9 Use this to predict the final exam score of a student who studies 4.5 hours per week, and please round your answer to a whole number.
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=-1.328 b=37.715 r?=0.788544 r=-0.888 Use this to predict the number of situps a person who watches 0.5 hours of TV can do (to one decimal place)
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: ý=ax+b a=-0.873 b=26.236 r2=0.527076 r=-0.726 Use this to predict the number of situps a person who watches 11 hours of TV can do (to one decimal place)
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=-0.889 b=31.442 r²=0.3721 r=-0.61 Use this to predict the number of situps a person who watches 4 hours of TV can do (to one decimal place)
The following table shows the number of hours of safety training at a large industrial plant for each of 6 divisions within the plant and the number of work hours lost due to accidents. X: Hours of safety training 10 19 30 50 65 80 Y: Work hours lost 80 65 68 35 10 12 a. Determine the Pearson's Coefficient of Correlation for the given data. Answer rounded to two decimal places b. Which of the following is an apporpriate comment for the correlation between X and Y? There is a strong positive correlation between X and Y There is a moderate positive correlation between X and Y There is a weak positive correlation between X and Y There is a strong negative correlation between X and Y There is a moderate negative correlation between X and Y
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=-1.324 b=23.586 r2=0.887364 r=-0.942 Use this to predict the number of situps a person who watches 11.5 hours of TV can do (to one decimal place)
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (x) and number of sit ups a person can do (y ). The results of the regression were: y=ax+b a=-1.33 b=25.138 r2=0.712336 r=-0.844 Use this to predict the number of sit ups a person who watches 10 hours of TV can do, and please round your answer to a whole number.
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 = a x + b a = -1.043 b = 29.088 %3D %3! r2 = 0.390625 r = -0.625 Use this to predict the number of situps a person who watches 6.5 hours of TV can do. situps : %3D [one decimal accuracy1

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