Consider the following computer output for a linear regression of height onweight:The regression equation isHeightPredictorConstantWeightCoefStdev0.15930.007385t-ratio13.3480-0.1560000.0000.00083.81-21.12s = 0.03873 R-sq = 98.2% R-sq(adj) = 98.0%The equation of the regression line is:A. Height = 13.35 + .03873 (Weight)B. Height = 13.35 + .1593 (Weight)O C. Height = 13.35 - .156 (Weight)D. Height = .1593 + .007 (Weight)O E. Height = - .156 + 13.35 (Weight)

Answered: Image /qna-images/answer/7afebcb0-f376-4495-ad39-a42878702984.jpg

Answered: Consider the following computer output…

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 study per week (z) and the test scores (y)- The results of the regression were: y=ax+b a=5.701 b=31.89 r2=0.660969 r=0.813 Use this to predict the final exam score of a student who studies 3.5 hours per week, and please round your answer to a whole number. Question Help: Message instructor Submit Question rse here to search R
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)
Interpret the intercept and the coefficients of D1 and D2 in the regression above.
Total plasma volume is important in determining the required plasma component in blood replacement therapy for a person undergoing surgery. Plasma volume is influenced by the overall health and physical activity of an individual. Suppose that a random sample of 50 male firefighters are tested and that they have a plasma volume sample mean of x = 37.5 ml/kg (milliliters plasma per kilogram body weight). Assume that ? = 7.20 ml/kg for the distribution of blood plasma.
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=-1.383 b=24.599 r2=0.962361 r=-0.981 Use this to predict the number of situps a person who watches 5.5 hours of TV can do (to one decimal place)
The dataset below contains synthetic records of human heights and weights of 18 years old children. HEIGHT WEIGHT (Feet) (in kg) 5.48 51.36 5.96 62.04 5.78 69.56 5.69 64.70 5.65 65.59 5.73 56.05 5.82 64.31 5.83 62.03 а. Find the equation of the regression that model the relationship between the weight of mail and number of order using LINEAR EQUATION, EXPONENTIAL EQUATION, SIMPLE POWER EQUATION, and HYPERBOLIC| EQUATION. b. Compute for the correlation coefficient of each equation using PEARSON PRODUCT MOMENT CORRELATION COEFFICIENT (PPMCC).
An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:. Summary measures Multiple R 0.9689 R-Square 0.9387 Adj R-Square 0.9212 StErr of Estimate 72.218 Regression coefficients Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.
The trip rate (y) and the corresponding household sizes (x) from a sample are shown in Table Q2. Apply the regression method to find the trip rate for a household size of 10. Table Q2
A regression was run to determine if there is a relationship between hours of TV watched per day (xx) and number of situps a person can do (yy). The results of the regression were: y=ax+ba=-1.392b=32.952r2=0.527076r=-0.726Use this to predict the number of situps a person who watches 2 hour(s) 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=ax+b a=-0.666 b=36.053 r2=0.552049 r=-0.743 Use this to predict the number of situps a person who watches 4.5 hours of TV can do (to one decimal place)
The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). Which regression equation is best for predicting city fuel consumption? Why? E Click the icon to view the table of regression equations. Choose the correct answer below. O A. The equation CITY = 6.65 - 0.00161WT + 0.675HWY is best because it has a low P-value and the highest adjusted value of R2. O B. The equation CITY = 6.83 - 0.00132WT - 0.253DISP + 0.654HWY is best because it has a low P-value and the highest value of R?. OC. The equation CITY = 6.83 - 0.00132WT - 0.253DISP + 0.654HWY is best because it uses all of the available predictor variables. O D. The equation CITY = - 3.14 + 0.823HWY is best because it has a low P-value and its R2 and adjusted R? values are comparable to…

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