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# MAT 240 D.M. Pan National Real Estate Company Part 2

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D.M. Pan National Real Estate Company
D.M. Pan National Real Estate Company Part II
Ashley Allen
Southern New Hampshire University
D.M. Pan National Real Estate Company
Module Two Notes
In order to give the D.M. Pan National Real Estate Company competitive advantage in
the sale of households, this report provides an intuitive analysis. Immobilizing agents must be
well versed in the price, square film, year, site and many others which can help predict the
business world and provide their customers with the best advice. Another aim of this report is to
examine the relationship between property selling prices and the square feet of the property. The
Real Estate County Data document provided me with, which gave me details about which
properties have been sold nationwide in recent years.
Regression Equation
I used the regressive expression y= 968x*511 to determine the slope and intercept. The
path is 968 and the intercept is 511 based on this regression equation.
Determine r
R is 0.9607 in value. This means that the median price and the median square feet have a
moderately positive linear relationship. I used the = CORREL formula to find the value of r.
Correl function in excel is used to calculate the correlation coefficient which only has a value of
-1 to +1 and also shows the connections between any 2 values. It is because there are only -1 to
D.M. Pan National Real Estate Company
+1 in the range for the correlation coefficient, which is rather small and the value falls within this
range less than any other number. The higher the list price, the larger the square image is, the
higher the list price.
Examine the slope and Intercepts
When determining the value of the land only, it will be difficult to draw a conclusion. The
slope is 0.968, and the intercept is 511. The values of the quadrant images and the pricing square
images are indicated. At this point, I cannot determine just the value of the land without any
R-Squared Coefficient
For every 100 square feet, R-squared means how much the price rises in the context of
this analysis. In this case, I found that the price rose by 968 per 100 square feet. For linear
regression models R-squared is a fitness-of-mechanism. This figure shows the percentage of
variance that the independent variables collectively explain. You have to determine how well the
model matches the data after you fit a linear regression model.
Conclusion
I compare square feet with the price in the region I chose. Compared to all homes in the
United States, the western south-central region is similar in the mean and median list prices and
close to the square. By analyzing how the paths can help detect price changes, this can help to
determine how a home should be listed for sale by quadratic images. The regression equation can
help to identify suitable prices based on the square footage.
D.M. Pan National Real Estate Company
References
“CORREL Function - Formula, Examples, Calculate Correlation in Excel.” Corporate Finance
Institute, 26 June 2019,
corporatefinanceinstitute.com/resources/excel/functions/correl-function-correlation/.
Frost, Jim, et al. “How to Interpret Adjusted R-Squared and Predicted R-Squared in Regression
Analysis.” Statistics By Jim, 24 Oct. 2019,