Construct a 95% confidence interval of the population average square footage (SQ_FT). Interpret the confidence interval in the context of the problem. You have to show your work in order to earn full credit.

You currenty own a home in Eastville. Oregon, and want to put your bouse on the market. You're not in any particelar herry to get nid of the house. and would like io try selling it yourself. One way to determine a reasonable asking price of a house is to call one or more real estate agents and seek their advice. Anoher is oo hire an appeaiser-this appeoach would cost several hundred dollars. You've been woedering if there might be an easier and cheaper way to understand what determines selling prices in the area. On yoar daily after-dinner stroll through the neighborhood, you've passed several houses on the market. At first, you hoped that you could get a feel for the market by simply studying these few houses. But the more you think about this problem, the more confused you get. You're pretty sure that bigger homes sell for more, bul yoa doa't know how much more. Also, it seems as if fireplaces would be a desirable amenity in Oregon; your house doesn't have a fireplace, and you're not sure how much to lower the asking price because of this. You've also heard that location is the most important thing in the real estate market, and you wonder if prices tend to vary by school district, one indication of the quality of the neighborhood. A friend has collected some information for yoa aboat selling prices and other char acteristics of houses sold within the last few nonths in your neighborhood. These inclede square feet, aumber of bedrooms and bathrooms, type of heating, and sehool district. This data set is shown below. At first, you decided that your problem was solved-you would only need to find a house just like yours in the dera set, and ase iss price as your guess. Of course, it's never that easy. Although you know the specific eharacteristics of your house, such as squae feet, number of bedrooms and bathrooms, and so forth, nor These duta were used by Ellen L. Chilias, David S. Abelson, and Drian R. Landry to price a house owned by one of the goep members as part of a stadent frojec. The name of the subarb from which the dana were taken has been changed. one of the howses in the data set is a perfect masch for your awn lome. Some of the houses in the data set coene close to yours, but every comparable house is different from yours is at least theee aspects. You're wondering if there might not be another way to use the data to come up with an estimate. The data are contained in the file named HOUSES, which includes information on 108 houses. In this data set, SQ.FT is the variable measuring the total square foet in the house. BEDS and BATHS are eumber of bedrooms and bathrooms, respectively. HEAT and STYL.E are categorical variables. HEAT takes on the value of 0 for gas forced air heatieg and I for electric heat. STYLE is the architectural style of the home: 0 indicates a trilevel. I indicates a two-story house, and 2 indicates that the hosse is a ranch-styled bome. GARAGE is the Eumber of cars that might fit in the garage, althosgh yoe doa't know whether the garage is attached. AGE is the age of the house in years. FIRE indicates the presence (FIRE =1 ) or absence (FIRE =0 ) of a fircplace and BASFMENT indicates the presence (BASHMENT = 1) or absence (BASEMANT =0 of a basement. PRICE is the selling prioe of the house in thousands of dollars and SCHOOL. is the shool district ( 0 = Eastville school divtrict; I = Apple Valley school district). All elie the same, Apple Valley is viewed as being the more desirable of the two school districts. Use these data to uncover the important determinants of selling prices of hosass in your ncighbortood. Then prepare a description of how your findings might be esed as a general method for estimating the selling price of any house in your neighborhood, such as yours. (12) cuse at nousig paces-4 11-11 (eonelusw on the next page) II-12 CASE as Housins Aices-a You currenty own a home in Eastville. Oregon, and want to put your bouse on the market. You're not in any particelar herry to get nid of the house. and would like io try selling it yourself. One way to determine a reasonable asking price of a house is to call one or more real estate agents and seek their advice. Anoher is oo hire an appeaiser-this appeoach would cost several hundred dollars. You've been woedering if there might be an easier and cheaper way to understand what determines selling prices in the area. On yoar daily after-dinner stroll through the neighborhood, you've passed several houses on the market. At first, you hoped that you could get a feel for the market by simply studying these few houses. But the more you think about this problem, the more confused you get. You're pretty sure that bigger homes sell for more, bul yoa doa't know how much more. Also, it seems as if fireplaces would be a desirable amenity in Oregon; your house doesn't have a fireplace, and you're not sure how much to lower the asking price because of this. You've also heard that location is the most important thing in the real estate market, and you wonder if prices tend to vary by school district, one indication of the quality of the neighborhood. A friend has collected some information for yoa aboat selling prices and other char acteristics of houses sold within the last few nonths in your neighborhood. These inclede square feet, aumber of bedrooms and bathrooms, type of heating, and sehool district. This data set is shown below. At first, you decided that your problem was solved-you would only need to find a house just like yours in the dera set, and ase iss price as your guess. Of course, it's never that easy. Although you know the specific eharacteristics of your house, such as squae feet, number of bedrooms and bathrooms, and so forth, nor These duta were used by Ellen L. Chilias, David S. Abelson, and Drian R. Landry to price a house owned by one of the goep members as part of a stadent frojec. The name of the subarb from which the dana were taken has been changed. one of the howses in the data set is a perfect masch for your awn lome. Some of the houses in the data set coene close to yours, but every comparable house is different from yours is at least theee aspects. You're wondering if there might not be another way to use the data to come up with an estimate. The data are contained in the file named HOUSES, which includes information on 108 houses. In this data set, SQ.FT is the variable measuring the total square foet in the house. BEDS and BATHS are eumber of bedrooms and bathrooms, respectively. HEAT and STYL.E are categorical variables. HEAT takes on the value of 0 for gas forced air heatieg and I for electric heat. STYLE is the architectural style of the home: 0 indicates a trilevel. I indicates a two-story house, and 2 indicates that the hosse is a ranch-styled bome. GARAGE is the Eumber of cars that might fit in the garage, althosgh yoe doa't know whether the garage is attached. AGE is the age of the house in years. FIRE indicates the presence (FIRE =1 ) or absence (FIRE =0 ) of a fircplace and BASFMENT indicates the presence (BASHMENT = 1) or absence (BASEMANT =0 of a basement. PRICE is the selling prioe of the house in thousands of dollars and SCHOOL. is the shool district ( 0 = Eastville school divtrict; I = Apple Valley school district). All elie the same, Apple Valley is viewed as being the more desirable of the two school districts. Use these data to uncover the important determinants of selling prices of hosass in your ncighbortood. Then prepare a description of how your findings might be esed as a general method for estimating the selling price of any house in your neighborhood, such as yours. (12) cuse at nousig paces-4 11-11 (eonelusw on the next page) II-12 CASE as Housins Aices-a