# 2hw11 - This shows that the variables being analyzed cannot account for the variation in housing cost This shows that the variables and not

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2. To analyze the data I found a simple linear regression of each data category against the house prices. I also found a multiple linear regression of the data categories combined versus the house prices. Below are the regression plots for the linear regression lines. The R^2 values were as follows: For price v bedrooms .279 For price v bathrooms.2698 For price v square feet .459 For price v all .463 As can be seen, all three graphs do seem to have a random distribution. The Coefficients of determination were all relatively low values.
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Unformatted text preview: This shows that the variables being analyzed cannot account for the variation in housing cost. This shows that the variables and not randomly distributed either. The price is not strongly related to # of bedrooms/ bathrooms, square feet, or a combination of the three. There is a closer degree of correlation for the combination of variables vs the housing price, but it is not a strong enough correlation to draw a significant conclusion that there is a relationship....
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## This note was uploaded on 01/24/2011 for the course ENME enme392 taught by Professor Cukier during the Spring '10 term at Maryland.

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