The following MINITAB output is for a multiple regression. Something went wrong withthe printer, so some of the numbers are missing. Fill in the missing numbers.PredictorCoefSECoef(a)0.086(b) 4.300.005(c) 0.3944-0.620.560Constant-0.58762 0.2873X11.5102X2(d)0.003R-Sq(adj) = 85.3%ХЗ1.8233 0.3867R-Sq =90.2%0.869Analysis of VarianceSS MS F P3 41.76 (e) (f) 0.000(g) 0.76(h) 46.30SourceDFRegressionResidual Error6.Total

Answered: Image /qna-images/answer/cc2c1f0c-2a7f-4fb1-9355-7262791df848.jpg

Answered: The following MINITAB output is for a…

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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An electronics retailer used regression to find a simple model to predict sales growth in the first quarter of the new year (January through March). The model is good for 90 days, where x is the day. The model can be written as follows: ŷ = 101.32 + 2.48x where ŷ is in thousands of dollars. What would you predict the sales to be on day 61?
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=-1.223 b=22.907 r2=0.600625 r=-0.775 Use this to predict the number of sit ups a person who watches 5 hours of TV can do, and please round your answer to a whole number.
Draw the regression line for the following equation: Y = -3 + (1) X Show your calculation for a low and high value on the predictor value.
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=-0.96 b=35.944 r2=0.736164 r=-0.858 Use this to predict the number of situps a person who watches 10.5 hours of TV can do (to one decimal place)
Suppose the estimaited OLS regression is: Happiness = a + b*dailychocolates Now use chocolate consumprion per week instead of days. What is the relationship between the old and new units? How would this affect b (i.e. what is bnew in terms of b)?
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=-0.96 b=35.944 r2=0.736164 r=-0.858 Use this to predict the number of situps a person who watches 10.5 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=-1.131 b=37.124 r2=0.398161 r=-0.631 Use this to predict the number of situps a person who watches 6.5 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 (2) and number of sit ups a person can do (y). The results of the regression were: y=ax+b a=-0.666 b=21.511 72=0.543169 r=-0.737 Use this to predict the number of sit ups a person who watches 7 hours of TV can do, and please round your answer to a whole number. Hìnt: Help Question Help: Message instructor Submit Question 围 hp Ce %23 & 3. 4. 6. 8. W e y 61
Write down the different Multiple Regression Equations?
A real estate analyst has developed a multiple regression line, y = 60 + 0.068 x1 – 2.5 x2, to predict y = the market price of a home (in $1,000s), using independent variables, x1 = the total number of square feet of living space, and x2 = the age of the house in years. The regression coefficient of x2 suggests this: __________. If the square feet area of living space is kept constant, a 1 year increase in the age of the homes will result in a predicted drop of $2500 in the price of the homes If the square feet area of living space is kept constant, a 1 year increase in the age of the homes will result in a predicted increase of $2500 in the price of the homes Whatever be the square feet area of the living space, a 1 year increase in the age of the homes will result in a predicted increase of $2500 in the price of the homes Whatever be the square feet area of the living space, a 1 year increase in the age of the homes will result in a predicted drop of $2500 in the price of the homes
A sports-equipment researcher was interested in the relationship between the speed of a golf club (in feet per second) and the distance a golf ball travels (in yards). Information was collected on several golfers and was used to obtain the regression equation ŷ = 2x - 106, where x represents the club speed and ŷ is the predicted distance. Which statement best describes the meaning of the slope of the regression line? For each increase in distance by 1 yard, the predicted club speed increases by 2 ft/sec. For each increase in distance by 1 yard, the predicted club speed decreases by 106 ft/sec. For each increase in club speed by 1 ft/sec, the predicted distance increases by 2 yards. For each increase in club speed by 1 ft/sec, the predicted distance decreases by 106 yards.
One home that is 1092 square feet is listed at $189,900. What is the residual at x = 1092?

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