coeffiicent of age is -581
so, answer is
decrease the average selling price by $581
A home appraisal company would like to develop a regression model that would predict the sling...
A home appraisal company would like to develop a regression model that would predict the selling price of a house based on the age of the house in years (Age), the living area of the house in square feet (Living Area) and the number of bedrooms (Bedrooms). The given Excel output shows the partially completed regression output from a random sample of homes that have recently sold. How many homes were included in the sample? EEB Click the icon to...
The following is Excel output from a fitted linear regression model relating the sale price of a home (Y, in thousands of dollars) to age of the home (X) in years. Intercept Age Coefficients 213.365436 - 1.207517218 Standard Error Stat P-value 1.450657792 147.0819 0 0.029970869 -40.2897 1.2E-278 Lower 95% Upper 95% 210.5209309 216.2099411 -1.26628524 -1.148749195 Refer to the information above on the regression using age to predict selling price. Which of the following gives the 95% confidence interval for by...
1. One Price Realty Company wants to develop a model to estimate the value of houses in its inventory The office manager has decided to develop a multiple regression model to help explain the variation in house values. (25 points) The office manager has chosen the following variables to develop the model: X1 square feet X2- age in years x3- dummy variable for house style (1 if ranch, 0 if not) X4-2d dummy variable for house style (I if split...
A hospital would like to develop a regression model to predict the total hospital bill for a patient based on his or her length of stay, number of days in the hospitais intensive care una (CU), and age of the patient Data for these variables can be found in the accompanying table Complete parts (a) through (e) below. Click the icon to view the data table a) Using technology, construct a regression model using all three independent variables, where y...
A hospital would like to develop a regression model to predict the total hospital bill for a patient based on the age of the patient (x1), his or her length of stay (x2), and the number of days in the hospital's intensive care unit(ICU) (x3). Data for these variables can be found below. Complete parts a through e below. a) Construct a regression model using all three independent variables. (Round to the nearest whole number as needed.) b) Interpret the...
A real estate agent wants to use a multiple regression model to predict the selling price of a home in thousands of dollars) using the following four x variables. Age: age of the home in years Bath: total number of bathrooms LotArea: total square footage of the lot on which the house is built TotRms_AbvGrd: total number of rooms (not counting bathrooms) in the house The agent runs the regression using Excel and gets the following output. Some of the...
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...