Lamar University
Memo
To:
Dr. Wendi Malley
From: Ashley Flores and Jesus “Jesse” Valdez
Date:
09/30/2020
Re:
Carolina Park Subdivision Analysis
Introduction
The price of a home is what a buyer is willing to pay for a home that is in the open market.
The price will vary depending on what type of house it is and its square footage.To find out if
there is a correlation between the price of a home and its square footage, we decided to
study the Carolina Park Subdivision. We are studying this because we find it interesting to
examine if there’s a specific type of connection between home prices and its size for anyone
interested in purchasing a home.
Descriptive Statistics
The mean incidence for the list price of homes in the Carolina Park Subdivision is
$560,015, and the standard deviation is $94,018.37. The median of the house's prices is
$549,900. Of the listed home values, the minimum is $369,900, and the maximum is
$835,900. At least 25% of the data is below $507,450, at least 50% of the data is below
$549,900, and at least 75% of the data is below $589,900. The following list prices are
outliers: $369,900, $375,000, $725,900, $729,900, $769,900, $775,000, $835,900. Outliers
are points (the prices of the homes) that fall more than 1.5 times the interquartile range
above the third quartile ($589,900) and below the first quartile ($507,450).
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Bivariate Analysis
Reviewing the Summary Output report, no houses had 0 square feet, so b 0 =
186303.3549 just indicates that, for houses within the range of sizes observed, $186,303.35
is the portion of the house price not explained by square feet. So, it has no meaning. Here,
b1 = 141.6526546 tells us that the average value of a house increases by 141.6526546
($1000) = $141.65, on average, for each additional one square foot of size. Utilizing the
Bivariate Analysis graph, there is a weaker linear relationship between x (square footage)
and y (home prices) and some but not all of the variation in y (home prices) is explained by
variation in x (square footage). The variation in house prices is explained by variation in
square feet is 88.66% with the Slope of the model being 141.6527. The Test Statistic is
7.1267 indicating there is sufficient evidence that square footage affects house price. At
95% level of confidence, the confidence interval for the slope is (101.6669, 181.638). Since
the units of the house price variable is $1000s, we are 95% confident that the average
impact on sales price are between $101.67 and $181.64 per square foot of the house. This
95% confidence interval does not include 0.
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Conclusion
Based on our findings, we can conclude that there is in fact a correlation. We found
out that there were seven outliers in our data that either fall below $507,450 or above
$589,900 of the home’s price range. There is a significant relationship between house
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price and square feet at the 0.05 level of significance. There is a weaker, positive linear
relationship which helps us understand that when the square footage increases in a
home, so does the house price. If the square footage decreases, the house price tends
to go down. For any potential buyer out there, the size of a home could impact its value
price.
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