A property appraiser wants to find a multiple regression model to describe the r

Question

A property appraiser wants to find a multiple regression model to describe the relationship between the following variables: Y = the sale price (in dollars) of a residential property in a mid-sized city, X1 = the appraised land value of the property (in dollars), X2 = the appraised value of the home (in dollars), and X3 = the area of living space in the home (in square feet). A random sample of 20 properties was selected from all the properties that were sold in a particular year. a) The following scatter plots are plotted below: the sale price versus the appraised land value, the sales price versus the appraised home value, and the sales price versus the area of living space. For each plot the correlation between the two variables is also computed. Comment on the plots. What is you assessment of using the independent variable to help predict the sales price?

Pearson correlation of Sale Price and Land Value = 0.790

Pearson correlation of Sale Price and Home Value = 0.916

Pearson correlation of Sale Price and Area = 0.849

Choose the best answer from the following:

i) These plots suggest: 1) a change in the appraised land value will cause a change in the sales price, 2) a change in the appraised home value will cause a change in the sales price, and 3) a change in the area of living space will cause a change in the sales price. Scatterplot of Sale Price vs Land Value 120000 80000 R60000 40000 20000 CD 10000 15000 25000 Land Value

Explanation / Answer

V)Both ii) and iii) are correct

Becuaze we see all the three plots are positively correlated

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