The following Minitab display gives information regarding the relationship between the body weight of a child (in kilograms) and the metabolic rate of the child (in 100 kcal/hr).PredietorCoefSE CoetConstant0.85700.41482.060.04Weight0.302430.0297813.520.000B0.51750eR-Bg 97.4(a) Write out the least-squares equation.(b) For each 1 kilogram increase in weight, how much does the metabolic rate of a child increase? (Use 5 decimal places.)(c) What is the value of the correlation coefficient ? (Use 3 decimal places.)

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Answered: hr). weight of a child (in kilograms)…

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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You are asked to estimate the model wage=B1+B2 EDU+ B3 EDU? where wage is the hourly wage ($) and EDU is the number of years of education. OLS results from a sample of 1000 university graduates are reported below: Wage=9.79-1.20 EDU+0.089 EDU2; R-square%-D0.23 se (2.67) (0.40) (0.09) Test the hypothesis that the expected effect of an extra year of education on hourly wage of an individual with 12 years of education is $1 against the alternative that it is less than $1 at 5% significance level (show all work). You are given the se(b2+2"b3 EDU)=D 0.045 Paragraph BI II
A least squares regression line was calculated to relate the length (cm) of newbom boys to their weight in kg. The regression analysis gives the model Weight = -5.11 +0.1952 Length. Complete parts a through c below. O D. For every additional 1 kg of weight, the length of the baby is predicted to increase by 0.1952 mm. b) If a baby is 53 cm long, what is his predicted weight? O kg (Round to two decimal places as needed.) c) Consider a baby boy that was 48 cm long and weighed 3 kg. According to the regression model, what was his residual? What does that say about him? The residual is . (Round to two decimal places as needed.) This means that the baby is kg V than predicted by his length. (Round to two decimal places 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=-0.696 b=30.652 r=0.603729 r=-e.777 Use this to predict the number of situps a person who watches 13.5 hours of TV can do (to one decimal place) Question Help: Message instructor
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=-0.76 b=21.83 r2=0.659344 r=-0.812 Use this to predict the number of situps a person who watches 4 hours of TV can do (to one decimal place)
A6
A regression of average monthly expenditure (AME, measured in euros) on average monthly income (AMI, measured in euros) using a random sample of college-educated full-time workers earnings €100 to €1.5 million yields the following: AME = 710.7 + 8.8 × AMI, R2 = 0.030, SER = 540.30 d. What does the regression predict will be the expenditure of a person with an income of €100? With an income of €200? e. Will the regression give reliable predictions for a person with an income of €2 million? Why or why not? ( f. Given what you know about the distribution of earnings, do you think it is plausible that the distribution of errors in the regression is normal? (Hint: Do you think that the distribution is symmetric or skewed? What is the smallest value of earnings, and is it consistent with a normal distribution?).
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=-1.307 b=32.392 r²=0.675684 r=-0.822 Use this to predict the number of situps a person who watches 12.5 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: ŷ = a + bx a = 36.694 b = 0.874 R = = 0.923521 a) Use this to predict the number of situps a person who watches 0.5 hours of TV can e do (to 3 decimal places) b) What is the value of the correlation coefficient (to 3 decimal places) ? Priv Terr ост 21 MacBook Pro esc F1 F2 F3 F4 F5
Q12 a) Construct a regression model to determine the relationship between individual yearly income and the value of the car owned. b) Using the regression equation from (a) determine the value of the car if the yearly income is $40,000 c) Describe the relationship between yearly income and value of the car owned d) Identify the independent variable and dependent variable based on the regression model constructed in (a) e) Explain why it is incorrect to predict the value of the car if an individual income is $10,000
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=-0.971 b=21.794 r²-0.872356 r=-0.934 Use this to predict the number of situps a person who watches 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:y=ax+b a=-0.982 b=31.084 r2=0.471969 r=-0.687 Use this to predict the number of situps a person who watches 13.5 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: y=ax+b a= -0.889 b=32.071 r2=0.505521 r= -0.711 Use this to predict the number of situps a person who watches 5 hours of TV can do (to one decimal place)

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