Assignment 3-3
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Southern New Hampshire University *
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240
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Mathematics
Date
Apr 3, 2024
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docx
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Uploaded by brejaaaa
1
Housing Price Prediction Model for D.M. Pan National Real Estate Company
LaBreja Graham
Department of Math, Southern New Hampshire University
MAT 240: Applied Statistics
Sonal Patel
1/28/2024
2
Housing Price Prediction Model for D.M. Pan National Real Estate Company
Module Two Notes
[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
Y=104.08x+53707
Determine r
r = 0.84 this means it’s a strong correlation between the square footage and listing price of the properties because the number is closer to 1. As the square footage increases the listing price also increases, this creates a positive association between the two variables. Examine the Slope and Intercepts
The intercept is 53707, when the regression line crosses the y-axis it’ll be at this point. This means that when the square feet area is 0 the listing price should be 53707. The slope is 104.08, when the square footage area increases by one unit the listing price increases by $104.08 each unit.
R-squared Coefficient
R
-squared = 0.70672 . The correlation is how much the listing price is varying explained by how much the square feet is varying. Almost 71% of the variation in listing price is explained by variation of square feet.
Conclusions
sq ft
National
ENC region
listing national
ENC
3
price
region
mean
2111
1611
mean
342365
221397
median
1881
1561
median
31800
217700
stand. Dev
921
445.3114
stand. Dev
125914
55129.95
min
1101
1113
min
135300
148700
q1
1626
1401.75
q1
265250
192700
q3
2215
1692.75
q3
381600
236675
max
6516
3581
max
987600
461400
Above are the two charts Ive made in a spreadsheet to show the comparison of the square footage and listing pricing of my East North Central region to the National average. The slope can identify
price ranges for listings based off of the square footage of the house, for every unit a square footage moves up or down, the listing price will accommodate for the changes based on the regression line. This also shows how to list a house, if a house is 180,000 square feet in that region you’ll use the equation from the regression line to price the house by plugging 180,000 in as x
. y = 104.08 (180,000) + 53707. The range can be good for 1,000 square feet through 2,000 square feet.
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