March 24, 2024
Module Two Notes
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[Copy and paste any relevant information from your Module Two assignment here to assist you in completing this assignment. This section is not graded and is only provided to help you easily review Module Two assignment information while completing this assignment.]
Regression Equation
Figure 1
Scatterplot of Listing Price against Property Size
The regression equation is y = 94.286x + 61,430.
Determine r
The correlation coefficient is 0.9441. There is a very strong and positive linear relationship between property size and listing price.
Examine the Slope and Intercepts
The slope is 94.286; a change in the property size by one square foot results in a correspondent change in the listing price by $61,430. The intercept is $61,430; this is the value of the land with no property on it.
R-squared Coefficient
The value of the r-squared is .8914; the variability in the property size can be used to explain 89.14% in the variability of the listing price.
Conclusions
The purpose of this analysis was to determine whether there is a linear relationship between property size and listing price. The relationship between the two is positive; as the size of the property increases, the listing price will also increase and vice versa. The coefficients of the sample differ from the coefficients of the national data. First, the slope of the national data is 112.7 whereas that of the sample is 94.286. On the other hand, the intercept of the national data is 104,468 whereas that of the sample is 61,430. Despite the differences, both depict positive relationships.