Using the package “wooldridge’, and the data ‘hprice1’ (in R-Software) to estimate the model price = β0 + β1sqrft + β2bdrms + u , where is the house price measured in thousands of dollars.
1. Write out the results in equation form.
2. What is the estimated increase in price for a house with one more bedroom, holding square footage constant?
3. What is the estimated increase in price for a house with an additional bedroom that is 140 square feet in size? Compare this to your answer in part 2
1)
price ^ = −19.31 + 0.13 sqrf t + 15.20bdrms
2)
One more bedroom is estimated to increase the sales price by $15,200
3)
Adding a bedroom without increasing the size of the house at all results in an increase in price of $15,200. Doing so essentially means that you would be adding a bedroom (which takes up some number of square feet) and subtracting that number of square feet from elsewhere in the house (so that you gained a bedroom without adding any square feet). If we now add a bedroom and 140 square feet to a house, we increase its predicted sales price by 0.13 × 140 + 15.20 × 1 = 33.4, or $33,400
Using the package “wooldridge’, and the data ‘hprice1’ (in R-Software) to estimate the model price =...
please show the steps and the
code to solve this in R, thank you
11. (10 marks) (using dataset: "hpricel", in R: data(hprice1, package-wooldridge')) Use the data to 5 estimate the model where price is the house price measured in thousands of dollars iWrite out the results in equation form. iiWhat is the estimated increase in price for a house with one more bedroom, holding square footage and lot size constant? iii What is the estimated increase in price for...
A regression analysis of 117 homes for sale produced the following model, where price is in thousands of dollars and size is in square feet. Price = 47.84 +0.067(Size) a) Explain what the slope of the line says about housing prices and house size. b) What price would you predict for a 3000-square-foot house in this market? c) A real estate agent shows a potential buyer a 1300-square-foot house, saying that the asking price is $6000 less than what one...
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this question in R
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10. (8 marks) (using dataset: "meap93", in R: data(meap93, package-'wooldridge)) We want to explore the relationship between the math pass rate (scil/) and average teachers' compensation (salary + benefits) in the school (totcomp) In the population model: scill,-β0 + βι log(totcompi-u, prove that β/ 10 is the percentage point change in scill given a 10% increase in totcom. ii Use the data in MEAP93 to estimate the...
2. Consider the following log-level regression using HPRICE1 log(price) = Be + Bisarft + B2bdrms + u Suppose you are interested in estimating and obtaining a confidence interval for the percentage change in price when a 150-square-foot bedroom is added to a house. In other words, two changes are occurring simultaneously: sarft is increasing by 150 (15031) to make one additional bedroom (B2). Define a suitable variable to reflect this change, altering the above model.
IL. (1Ipts) You are given the following estimated equation: log(price) =-0.676 + 0.848 log(sqrft)-0.05 1bdrrns-0.269colonial + 0.098bdrms * colonial Std. Errors (0.693) (0.1003) (0.060) n 88, R-squared -0.5793 (0.216) (0.0636) Where the variables are described as follows: price sarfi the size of the house, in squared feet hdrms the number of bedrooms in the house colonial- if the house has a colonial architectural style, and 0 otherwise. bdrms colonial interaction variable the house price, in $1000 a. Provide an appropriate...
One of the biggest factors in determining the value of a home is the square footage. The accompanying data represent the square footage and selling price (in thousands ofdollars) for a random sample of homes for sale in a certain region. Complete all parts below (A.) Which variable is the explanatory variable? a. selling price b. square footage Square Footage, x Selling Price ($000s), y 2221 382.7 3046 353.4 1175 197.2 1938 332.2 3166 630.2 2857 383.9 4086 623.6...
options C and D for the mutiple choice questions are
C: The selling price of this particular house is less than the
predicted value by the amount of the residual.
D: The residual is the predicted selling orice for house with
zero square feet.
For the response variable y, the selling price in thousands of dollars, and the expanatory variable x, the size of the house in thousands of square feet. ý = 9.5 +77 2x. a. How much do...
One of the biggest factors in determining the value of a home is the square footage. The accompanying data represent the square footage and selling price in thousands of dollars) for a random sample of homes for sale in a certain region. Complete parts (a) through (h) below. square feet, on average. Click the icon to view the housing data. D. For every additional thousand dollars in selling price, the square footage increases by (Round to three decimal places as...
II. (11pts) You are given the following estimated equation: log(price) 4.83+0.000347sqrft + 0.0117bdrms-0.056colonial +0.000068srft colonial Std. Errors (0.013) (0.000061) (0.0310) (0.015) (0.000074) n 88, R-square -0.6056 e tri Where the variables are described as follows: price = the house price, in $1000 sar-the size of the house, in squared feet bdrms the number of bedrooms in the house colonial- 1 if the house has a colonial architectural style, and 0 otherwise. sarfi colonial interaction variable Sser a. Provide an appropriate...
5. You want to examine how the median housing price (in dollars) in a community is related to the average lot size (square-feet) of houses in the community a) Suppose you want to estimate the percent change in median housing price when you increase the average lot size by one square-foot. Write out the regression model you would use, assuming that there is an intercept. b) Write out the formula for your estimate of the effect in part (a). c)...