Summary of Part A Number 3,4

Summary of Part A Number 3,4 - highly related to the age of...

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Ryan Scarff #0760906 Section AD, Raghav How is the age related to the selling price? The price and age of the houses can be related using the regression equation, Y=122.9463- 2.22179X. This equation is a tool that can be used to estimate the price of a house, Y, based on the age of the house, X. The intercept, $122.9463, of this equation, represents the estimated price of a brand new house (0 years old). The slope, -2.22179, of this equation represents the significance that 1 year of age has on the estimated price of a house. For example, one additional year might reduce the estimated price of a house by 2.22 thousand dollars. The scatterplot shows a visual interpretation of the data. It also reveals the negative correllation coefficient, -.3914. The strength of the correllation coefficient, .15317, is quite weak. This suggests that price is not
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Unformatted text preview: highly related to the age of the home. But it can be concluded that the older the home gets, the more likely it is to be less expensive. How is the type of heating (gas or electric) related to the selling prices? The estimated price of the houses does not appear to relate to the type of heating. This can be shown by the strength of the correllation coefficient, R^2, .0074. As it is very close to 0 we can conclude that the price is not strongly related to the type of heating. To affirm this assumption we can take the difference in the average price of the houses with gas heating the average price of the houses with electric heating. This difference, $11.96, is less that half standard deviation, $26.43. This shows that variance in the prices is such that the relation between the price and the type of heating is weak or nonexistant....
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This note was uploaded on 03/15/2010 for the course QMETH 201 taught by Professor Faaland during the Spring '08 term at University of Washington.

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