Suppose you want to estimate the effect of access to publictransportation on house prices. You write down the followingregression model:Price; = Bo + B₁ Distance; + B₂ Schoolį + Uiwhere Price; is the average house price in a community, indollars per square foot, Distance; is the distance in miles fromthe community to the nearest subway station, and School; isthe number of schools in the neighborhood.Your estimation yields ₁ = 1327. Suppose two communitiesdiffer in their distance to the nearest subway stops by 0.5miles but have identical characteristics otherwise. What is theexpected difference in the average house price between thetwo communities?663.5Not enough information given to answer the question13272652

Answered: Image /qna-images/answer/85b3216d-ae99-4fe8-8d70-c4f8d4d20341.jpg

Answered: Suppose you want to estimate the effect…

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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Market researchers were interested in the relationship between the number of pieces in a building-brick set and the cost of the set. The researchers collected information from a survey and used it to obtain the regression equation ŷ = 0.08x + 1.20, where x represents the number of pieces in a set and ŷ is the predicted price (in dollars) of the set. What is the predicted price of a set that has 2,520 pieces? $202.80 $2,017.20 $3,024.08 $31,485
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A researcher that there is a linear association between the level of potassium content (y) in milligrams and the amount of fiber (x) in grams in cereal. The regression line for the data is computed to y=37+28x rate. It was also computed that r=.59 A. What does the value . 59 tell you? B. What does the value 37 tell you? C. What does the value 28 tell you ? 2. For the line in question 1 what percentage of variability in potassium can be explained by variability in fiber?
Provide an example of a research project in your hometown where you would choose to use linear regression. What variable would be your Y-score, and what variable would be your X-score? What does a regression line represent? What is the standard error of estimate?
The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.
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). The equation CITY - 3.17 +0.823HWY was previously determined to be the best for predicting city fuel consumption. A car weighs 2700 lb, it has an engine displacement of 1.6 L, and its highway fuel consumption is 35 mi/gal. What is the best predicted value of the city fuel consumption? Is that predicted value likely to be a good estimate? Is that predicted value likely to be very accurate? Click the icon to view the table of regression equations. The best predicted value of the city fuel consumption is (Type an integer or a decimal. Do not round.). Regression Table I R² Adjusted R2 WT/DISP WT/HWY Predictor (x) Variables P-Value WT/DISP/HWY 0.000 0.942 0.000 0.748 0.000 0.942 0.000…
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In simple linear regression, the coefficient of determination measures: a.The amount of variability of the y variable that is explained by the x variable b.The amount of variability of the x variable that is explained by the y variable c.The amount of variability between the treatments d.The amount of variability within the treatments
If the equation of the regression line that relates income in dollars of student’s parents, xx, with cost in dollars of tuition,yy, is y=8500+0.018xy=8500+0.018x. a. What is the best prediction for the tuition of students whose parents earn no income? b. What is the best prediction for the tuition of students whose parents earn $45000? c. What is the best prediction for the tuition of students whose parents earn $80000?

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