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Interpret the pricing structure of houses in mid city

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Sales of single family houses have been brisk in Mid City this year.  This has especially been true in older, more established neighbourhoods, where housing is relatively inexpensive compared to the new homes being built in the new neighbourhoods.  Nevertheless there are also many families who are willing to pay a higher price for the prestige of living in one the newer neighbourhoods.  The file C10_02.xlsx contains data on 128 recent sales in Mid City.  For each sale, the file shows the neighbourhood (1, 2, or 3) in which the house is located, the number of offers made on the house, the square footage, whether the house is made primarily of brick, the number of bathrooms, the number of bedrooms, and the selling price.  Neighbourhoods 1 and 2 are more traditional neighbourhoods, whereas neighbourhood 3 is newer, more prestigious neighbourhood. 

Use regression to estimate and interpret the pricing structure of houses in Mid City.  Here are some considerations.

1) Do buyers pay a premium for a brick house, all else being equal?

2) Is there a premium for a house in neighbourhood3, all else being equal?

3) Is there an extra premium for a brick house in neighbourhood 3, in addition to the usual premium for a brick house?

4) For the purpose of estimation and prediction, could neighbourhoods 1 and 2 be collapsed into a single older neighbourhood?

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This task provides a clear working example of multiple regression analysis. A standard multiple regression analysis was performed between the dependent variable and two or more independent variables. Individual relationships between the independent and dependent variables: t = observed t value, significance level, effect size

Reference no: EM131358760

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