Descriptive Statistics and Relationships
Descriptive statistics involves organizing and summarizing data so that it can be understood easily. It provides basic information about the different variables available in a set of data and identifies potential relationships between variables. The most commonly used descriptive statistics today include measures of dispersion, measures of central tendency, shapes and distribution, and charts and graphs. By applying any of these, researchers can understand how data is distributed, which results in a better, more effective analysis.
Correlation
Variable |
Obs |
Mean |
Std. Dev. |
Min |
Max |
CV |
salesprice |
138 |
1774282 |
825409.5 |
1000000 |
4350000 |
0.465208 |
sqft |
138 |
5691.297 |
1694.75 |
3099 |
11704 |
0.297779 |
beds |
138 |
4.543478 |
1.004512 |
3 |
8 |
0.221089 |
baths |
138 |
5.797101 |
1.362476 |
4 |
11 |
0.235027 |
garage |
138 |
3.731884 |
1.645786 |
2 |
15 |
0.441007 |
pool |
138 |
0.891304 |
0.312391 |
0 |
1 |
0.350488 |
age |
138 |
11.2971 |
5.308593 |
0 |
26 |
0.469908 |
fireplaces |
138 |
2.746377 |
1.323905 |
0 |
7 |
0.482055 |
dom |
138 |
105.8043 |
110.8735 |
0 |
573 |
1.047911 |
summerlin |
138 |
0.492754 |
0.501769 |
0 |
1 |
1.018295 |
male |
138 |
0.572464 |
0.496523 |
0 |
1 |
0.867344 |
All the variables are numerical. While the variables pool, Summerlin, and males are categorical, all other variables are continuous.The average final sales price is $1,774,282 with a standard deviation of $825,409.5. Among the 11 variables, variable dom is maximum volatile as it has the highest coefficient of variation while, variable beds are least volatile as it has the lowest coefficient of variation. None of the variables has any missing values.
|
salesprice |
sqft |
beds |
baths |
garage |
pool |
age |
fireplaces |
dom |
Summerlin |
male |
salesprice |
1 |
|
|
|
|
|
|
|
|
|
|
sqft |
0.6857 |
1 |
|
|
|
|
|
|
|
|
|
beds |
0.2939 |
0.5814 |
1 |
|
|
|
|
|
|
|
|
baths |
0.5229 |
0.782 |
0.7425 |
1 |
|
|
|
|
|
|
|
garage |
0.3056 |
0.5709 |
0.3228 |
0.5192 |
1 |
|
|
|
|
|
|
pool |
0.0861 |
0.0586 |
0.0501 |
0.0164 |
-0.0287 |
1 |
|
|
|
|
|
age |
-0.4238 |
-0.2146 |
-0.1359 |
-0.2691 |
0.0551 |
0.1693 |
1 |
|
|
|
|
fireplaces |
0.2788 |
0.3763 |
0.1922 |
0.2343 |
0.0959 |
0.0035 |
0.1012 |
1 |
|
|
|
dom |
0.0691 |
0.1745 |
0.0615 |
0.0185 |
0.0782 |
-0.0765 |
-0.1046 |
0.0755 |
1 |
|
|
summerlin |
0.0912 |
-0.2845 |
-0.318 |
-0.2798 |
-0.0863 |
-0.168 |
0.068 |
-0.0962 |
-0.0199 |
1 |
|
male |
-0.0359 |
-0.0014 |
0.118 |
0.0219 |
-0.043 |
0.0747 |
0.0568 |
-0.044 |
-0.174 |
0.0314 |
1 |
As the above table shows, all variables except the age of the property and males show an inverse relationship with the sales price. Sales price varies directly in the same direction with changes in other variables. Intuition also suggests that as facilities in a house increases, sales final price should also increase. Hence, our findings are consistent with the intuition.Price vs Sqft

Above Scatter plot and positive slope of fitted trendline shows that as size increases, sales price also increases (also suggested by the positive correlation coefficient)
a. Price vs Bath

Above Scatter plotand positive slope of fitted trendline shows that as no. of bathrooms increase, sales price also increases (also suggested by the positive correlation coefficient)
b. Price vs Age

Above Scatter plotand negative slope of fitted trendline shows that as age increases, sales price decreases (also suggested by the negative correlation coefficient)
c. Price vs DOM

Above Scatter plot and slightly positive slope of fitted trendlineshows that as age increases, sales price also slightly increases (also suggested by the very small positive correlation coefficient)
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Contrasting Characteristics of homes in Summerlin and in Henderson
Table 3: Descriptive Statistics (Average Values)
Variable |
Summerlin |
Henderson |
Price |
1850420 |
1700320 |
Sqft |
5203.838 |
6164.829 |
Bed |
4.220588 |
4.857143 |
Bath |
5.411765 |
6.171429 |
Garages |
3.588235 |
3.871429 |
Pool |
0.8382353 |
0.9428571 |
Age |
11.66176 |
10.94286 |
Fireplace |
2.617647 |
2.871429 |
DOM |
103.5735 |
107.9714 |
Agent_Gender |
0.5882353 |
0.5571429 |
As table 3 shows, the average sales price and the average age of the property for Summerlin is more as compared to Henderson. Similarly, in Summerlin, there are more no. of male agents as compared to Henderson. Apart from these variables, all other variables such as the average size of the houses, no. of bedrooms, bathrooms, garage space, pool, and fireplace availability and, average days the home was in the market for sale is more for Henderson as compared to Summerlin.Regression analysis
The average price of sold homes (breakdown by Location and Gender)
|
Female Agents |
Male Agents |
Summerlin |
2.00E+06 |
1.70E+06 |
Henderson |
1.60E+06 |
1.80E+06 |
Full |
1808444 |
1748769 |
As Table-4 shows, in Summerlin, female agents significantly outperform male agents in terms of the sales price. While, in Henderson, male agents perform better than female agents. Overall, female agents outperform the male agents, which matches the findings of Josephine Fenton and Robert Villemaire.
Regression results
Table5:
a. As Table-5 shows, as expected, variables sqft, baths, pool, fireplaces, Summerlin show a positive relationship with the sales price.While opposite to expected, variables beds, pool, and dom show a negative relationship with the sales price.And, as expected variables, age and males show a negative relationship with the sales price.
b. As the Table-5 shows, the p-value for the coefficients of variables sqft, pool, age, and Summerlin is <0.05. i.e. we can say with 95% confidence that the coefficients are statistically significant. While for all other variables, the p-value is >0.05, hence, the null hypothesis (coefficient = 0) is not rejected and thus we can say that the coefficient is not statistically significant.
c. As Table-5 shows, the value of F-statistic for the model is 27.65 and the p-value is 0.000 (<0.05). i.e. we can say with 95% confidence that the model statistically significantly fits the data. Also, R2 for the model is quite high (0.685). i.e. goodness of fit of the model is also very good.
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Conclusion
As the above analysis shows, sales value is statistically significantly affected by the size of the house, pool availability, age of the property, and if the property is Summerlin or Henderson. While Size, pool availability, and location show a positive relationship with sales value while the age of the property shows a negative relationship with sales value.i.e. the price of a new property is higher as compared to the old one. Similarly, Table-4 shows, female listing agents produce greater returns as compared to males.