Relationship between variables and the correlation coefficient.
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A real estate broker hoped to develop an equation that could be used to predict the sales price of homes in a certain suburb. It seemed to him that the most important variables, since all the homes were in pretty much the same locale, were age of house, square feet, and number of bedrooms.
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X=7.1 Y=90.7 x=0.4 y=-0.2 Sigma x^2=87.76
Sigma y^2=2481.44 Sigma xy=408.62
Determine the relationship between sales price and age of house and determine the correlation coefficient.
Is the age of the house significant factor at alpha=0.05 in determining sales price? Explain
What does the fact that the correlation is less than 100% suggest?
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Solution Summary
The solution addresses a real estate broker hoped to develop an equation that could be used to predict the sales price of homes in a certain suburb. It seemed to him that the most important variables, since all the homes were in pretty much the same locale, were age of house, square feet, and number of bedrooms.
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The relationship between sales price and age is determined by the slope and intercept of the linear fit. The slope = Sigma xy/ Sigma x^2
<br>and the intercept=y-bar - slope*x-bar
<br>The correlation coefficient describes the strength of the linear relationship between sales price and age ...
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