Selling Price and Area Analysis for D.M. Pan National Real Estate Company
MAT-240-H3014 Applied Statistics
Southern New Hampshire University
Terrell McGhee
Introduction
This study was carried out by real estate industry to determine competitive advantage of smart businesses. Statistical test such as regression analysis and descriptive statistics were used where regression analysis was used to determine the relationship between the selling price of properties and their size in square feet while descriptive statistics was used to summarize the data. A random sample of 30 real estates were selected where their median listing price and median square feet were recorded to carry out the study.
Representative Data Sample
Results from table 1 showed the results of 30 random samples from Texas region
Table 1
median listing price($) median square feet
226000 1500
314000 1300
215000 1600
354000 1650
245000 1700
257000 1200
305000 1350
317000 2000
267000 1850
268000 1750
271000 1640
229000 1625
321000 1550
216000 1150
290000 1350
279000 1700
320000 1850
211000 1400
269000 1450
225000 1250
316000 1540
328000 1260
335000 1360
327000 1900
238000 1870
240000 2100
237000 1270
302000 1670
301000 1980
224000 2140
Descriptive statistics
According to Nick (2007), descriptive statistics is a statistical measure that summarizes data into measures of center and central tendency table below showed the summary of median listing price and median square feet.
Table 2
median listing price ($) median square feet
Mean 274900 Mean 1598.5
Median 270000 Median 1612.5
Standard Deviation 42842.4 Standard Deviation 278.336
Results from the above table showed that the mean of the median listing price was $274900 while that of median square feet was 1598.5. The median value of the listing price was $270000 with the median of square feet being 1612.5. Standard deviation can be described as a measure of variation of a given data value from the mean. The standard deviation of median listing price was 42842.4 while that of median square feet was 278.336.
Data Analysis
From the descriptive statistics it was clear that the average median listing price of $274900 from the study was lower compared to that of national market that was approximately $284600.The sample is a reflective of the national market since the mean value is almost the same to that of the national market. The sample was made random by selecting the various samples from different strata’s. This included dividing the target population into different groups called strata’s and randomly selecting the 30 samples from the various groups. A sample of 30 was large enough to be a good representation of the population.
Scatterplot
The Pattern
From the scatter plot, median square feet was the predictor variable while the median listing price was the response variable. This was because median square feet was independent thus it was used to predict the selling price of the real estates.
The graph showed that there existed a positive relationship between median square and median listing price thus an increase in area of real estates would lead to an increase in the selling price. There existed no outliers from the data set since the values are concentrated in the same area.
The regression equation from the graph was,
y = 8.7399x + 260929
Having an area of 1200 square feet, the selling price would be
Median listing price = 8.7399(1200) + 260929
=$271416.88
The regression equation was positive indication that increase in independent variable would lead to an increase in the dependent variable.
References
Nick, Todd G. (2007). “Descriptive Statistics”. Topics in Biostatistics. Methods in Molecular Biology. 404. New York: Springer. pp. 33–52.
Phillip D. (2010 – Essay Writing Service: Write My Essay by Top-Notch Writer). “Upper and Lower Bounds for the Sample Standard Deviation”. Teaching Statistics. 2 (3): 84–86
