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Economics 391 Project

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II. Data Description

The price of the varying houses ranged from $71,000 to $131,000 with a mean of $100,146.32. The standard error of the price of the homes was $13,298.79. These measurements were measured while observing 150 different homes throughout the course of the study. Several variables were thought to affect the price of a home; these included the location, size of the house, size of the lot, size of the garage, age of the house, number of bedrooms and bathrooms, the number of floors in the house, and exterior siding of the house. The size of a house directly corresponds to the price of a home. In the sample population the houses ranged from 945 to 3202 square feet with a mean of 1581.82 square feet and a standard error of 29.33599 measured in feet squared. Also, the lot size of each house was taken into account for the model. The population’s lot size had a mean and standard error of 303.8133 square feet and 145.9674 square feet respectively. This was a direct result of the range of data—0 to 701 square feet. Another important selling point in a house is the number of rooms specifically bedrooms and bathrooms. In the sample population a mean number of bedrooms were found to be 3.06 with a standard error of .041483 on a range of 2 to 5 bedrooms. In terms of bathrooms, the average amount of bathrooms for each house in the population was found to be 2.17. The lowest number of bathrooms found any of the houses was 1, and the highest 3.5. Age of each house was taken into account in the study as well. On average, the houses in the study were about 6 years old. The oldest house was 39 years old, but the majority of the houses were not yet a year old. Whether or not the house has brick siding instead of aluminum siding is an important factor to consider when shopping for a house. The information collected shows that in the population 119

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