Suppose you want to estimate the effect of access to publictransportation on house prices. You write down the followingregression model:Price;where 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.-Bo + B1 Distance; + B₂ Schoolį + uiSuppose your estimation yields ₁correct interpretation of this estimated value?= 1327. What is theAn additional mile in the distance to the nearest subway station isassociated with an increase of $1,327 dollars in the average houseprice per square foot, in communities with zero schools.An additional mile in the distance from a community to the nearestsubway station is associated with an increase in average houseprice of $1,327 dollars per square foot.An additional mile in the distance from a community to the nearestsubway station is associated with an increase in average houseprice of $1,327 dollars per square foot, keeping the number ofschools in the community constant.

The data is defined below as follows:From the information, given the data is,Where,Price denotes the…

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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Suppose Isabella has developed the following estimated regression equation for the price of an Edmonton condo, based off square footage size (in square feet). Price = 151000 + 48* (Square Footage) a) If someone wants to purchase an Edmonton condo with a size of 1010 square feet, how much should they expect to pay? Answer: dollars b) If they want to buy a condo that is 43 square feet bigger, then how much more money should they expect to pay? Answer: dollars c) Would the intercept be meaningful if this regression represents the average Edmonton condo? Yes No
If an estimated regression line has a y-intercept of 10 and a slope of -5, then when x = 0, the estimātēd value of y is: а. О b. -5 о С. 10 d. 5
The following multiple linear regression depicts the sales of Unilever Corporation: S = 10- 0.20P + 0.06TA + 0.08RA Where:S: Sales (Unit);P: Price ($/Unit);TA: Television advertising ($)RA: Radio advertising ($). 1. Interpret the slopes;2. Is television advertising more effective than radio advertising? Why or why not?3. What is the effect of a $1 increase in price, a $3 increase in TV advertising, and a $2decrease in radio advertising on sales?4. What is the effect of a $2 decrease in price, a $2 decrease in TV advertising, and a $4increase in radio advertising on sales?
A real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the space, the following variables are used in a multiple regression model. y = sales price (in thousands of dollars) x₁ = total floor area (in square feet) x₂ = number of bedrooms x3 distance to nearest high school (in miles) = The estimated model is as follows. =76+0.098x₁ +16x₂ - 8x3 Answer the questions below for the interpretation of the coefficient of X₂ in this model. (a) Holding the other variables fixed, what is the average change in sales price for each additional bedroom in a house? dollars (b) Is this change an increase or a decrease? O increase O decrease X
The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) mported by a country, for the last seven years. Construct and interpret a 95% prediction interval for the amount of crude oil imported by the this country when the amount of crude oil produced by the country is 5,508 thousand barrels per day. The equation of the regression line is y = - 1.120x + 15,839.271. Oil produced, x 5,684 5,654 5,452 5,157 5,061 5,030 5,826 9,680 10,041 10,154 10,121 10,060 Oil imported, y 9,304 9,105 Construct and interpret a 95% prediction interval for the amount of crude oil imported when the amount of crude oil produced by the country is 5,508 thousand barrels per day. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) and O A. We can be 95% confident that when the amount of oil produced is 5,508 thousand barrels, the…
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 = -3.14 +0.816HWY was previously determined to be the best for predicting city fuel consumption. A car weighs 2740 lb, it has an engine displacement of 1.5 L, and its highway fuel consumption is 40 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. Regression Table The best predicted value of the city fuel consumption is (Type an integer or a decimal. Do not round.) Predictor (x) Variables WT/DISP/HWY WT/DISP WT/HWY DISP/HWY WT DISP HWY P-Value R² 0.000 0.943 0.000 0.748 0.000 0.942…
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 = -3.14 +0.818HWY was previously determined to be the best for predicting city fuel consumption. A car weighs 2760 lb, it has an engine displacement of 2.2 L, and its highway fuel consumption is 34 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 Predictor (x) Variables P-Value R² Adjusted R² WT/DISP/HWY WT/DISP WT/HWY DISP/HWY 0.000 0.943 0.000 0.747 0.000 0.941…
The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) imported by a country, for the last 7 years. Construct and interpret a 98% prediction interval for the amount of oil imported by the country and the amount of oil produced by the country is 5,483 thousand barrels per day. The equation of the regression line is y = -1.194x + 16,234.906
Increase in sales (percent) An advertising firm wishes to demonstrate to its clients the effectiveness of the advertising campaigns it has conducted. The following bivariate data on twelve recent campaigns, including the cost of each campaign (in millions of dollars) and the resulting percentage increase in sales following the campaign, were presented by the firm. Based on these data, we would compute the least-squares regression line to be y = 6.16+0.18x, with x representing campaign cost and y representing the resulting percentage increase in sales. (This line is shown below, along with a scatter plot of the data.) Increase in sales, y Campaign cost, x (in millions of dollars) (percent) 3.02 6.91 7.2+ 1.92 6.80 3.83 6.85 6.8- 1.40 6.37 6.6 - 3.12 6.42 3.56 6.82 6.4- 4.06 6.94 6.2 1.64 6.56 6- 2.06 6.50 1.62 6.18 1.5 2.5 3.5 6.66 Campaign cost (in millions of dollars) 2.87 2.25 6.61 Send data to calculator Based on the firm's data and the regression line, complete the following. (a)…
A set of X and Y scores has SSX = 10, SSY = 36, and SP = 20. The regression equation for these scores will have a slope constant of 2. True or False
Using a sample of recent university graduates, you estimate a simple linear regression using initial annual salary as the dependent variable and the graduate's weighted average mark (WAM) as the explanatory variable. If the regression model has an estimated intercept of 3200 and an estimated slope coefficient of 550, what is the predicted starting salary of a student with a WAM of 64?
2. The table below lists the annual land-line phone cost per costumer: Year 2012 2013 2014 2015 Cost ($) a. 692 610 Find a linear regression model for this data b. Interpret the slope of the model 580 C. Predict the annual land-line phone cost per customer in 2022 495 2016 434

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