A realtor in Blacksburg, Virginia is using regression analysis to build a regression model for predicting...
A realtor in Blacksburg, Virginia is using regression analysis to build a regression model for predicting the selling price of houses sold in the Blacksburg area. The selling Price (in thousands of dollars) and Size (in square feet of heated/cooled floor space) of each house was recorded and the data analyzed in Minitab. Consider the Minitab output below in answering the questions that follow the output.
Regression Equation
Price = 78.4 + 0.10780 Size
a. Name the predictor variable in this problem. (2)
b. Estimate the selling price for a house with 2,500 sq. ft. of heated/cooled floor space in
the Blacksburg area. Give your final answer in $. (3)
Homework Answers
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A realtor in Blacksburg, Virginia is
using regression analysis to build a regression model for
predicting...
A Realtor is interested in modeling the selling price of houses based on the square footage, the ...
A Realtor is interested in modeling the selling price of houses based on the square footage, the age of the house, and the style. The data was collected in the two largest cities in Arkansas and is presented in an excel file. We need two indicator variables for the style of the house. I will choose Traditional as the base category lif the house is a rambler lif the house is victorian rambler Oif not Now use Minitab output to...
USE R SOFTWARE TO SOLVE THE PROBLEM and SHOW ALL YOUR WORK WITH CODE. Build the model one a multiple regression model including the living area (), number of bedrooms (), and number of fireplaces...
USE R SOFTWARE TO SOLVE THE PROBLEM and SHOW ALL YOUR WORK
WITH CODE.
Build the model one a multiple regression model including the
living area (), number of bedrooms (), and number of fireplaces ()
as predictor variables.
summary the statistic
Produce an ANOVA table. Report SST, SSR, and SSE , and their
corresponding degrees of freedom.
Model #2: a multiple regression model including the living
area, “Central Air” (an indicator variable coded as 1 if a house
has...
y2 36 49 1760 You are a personnel director and are interested in predicting the Number...
y2 36 49 1760 You are a personnel director and are interested in predicting the Number of Shares of Company Stock (V) using the Number of Years Employed with the Company (X). You randomly selected 8 employees and obtain the following summary data: EmplNum NumberShares (Y) YearsEmployed (x) - XY X² 1 350 2100 122500 2 415 7 2905 172225 3 22 8 64 48400 4 520 4680 81 270400 5 355 10 3550 126025 640 8320 169 409600 7...
Statistics
Y = listing priceX1 = interior floor space (square footage of the house)X2 = land size (square footage). This is usually represented by length of the front of the lot (in ft) X the depth of the lot (in ft). sizes range but a common lot size in Vancouver is 33 X 120. You will need to convert this to feet squared (area) before entering it into your spreadsheet (i.e., 3960)X3 = number of bedroomsX4 = number of bathroomsX5 =...
A Realtor is interested in modeling the selling price of houses based on the square footage, the age of the house, and the style. The data was collected in the two largest cities in Arkansas and is presented in an excel file. We need two indicator variables for the style of the house. I will choose Traditional as the base category lif the house is a rambler lif the house is victorian rambler Oif not Now use Minitab output to...
USE R SOFTWARE TO SOLVE THE PROBLEM and SHOW ALL YOUR WORK
WITH CODE.
Build the model one a multiple regression model including the
living area (), number of bedrooms (), and number of fireplaces ()
as predictor variables.
summary the statistic
Produce an ANOVA table. Report SST, SSR, and SSE , and their
corresponding degrees of freedom.
Model #2: a multiple regression model including the living
area, “Central Air” (an indicator variable coded as 1 if a house
has...
y2 36 49 1760 You are a personnel director and are interested in predicting the Number of Shares of Company Stock (V) using the Number of Years Employed with the Company (X). You randomly selected 8 employees and obtain the following summary data: EmplNum NumberShares (Y) YearsEmployed (x) - XY X² 1 350 2100 122500 2 415 7 2905 172225 3 22 8 64 48400 4 520 4680 81 270400 5 355 10 3550 126025 640 8320 169 409600 7...
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