Empirical Research Methods for Real Estate Market Analysis

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Empirical Research Methods for Business

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Answer 1
The real estate market conditions were analyzed by the researcher in the data analysis
segment. The dependence of selling price of properties on the distance of the house to the nearest
train station and the nearest bus stop was investigated. The report has been presented as follows.
Variable Exploration
a) Price
The selling price of the real estate properties (M = $ 886580. SD =$ 324950) was noted
to be approximately normally distributed (SKEW = 0.43). The median of selling price was
identified to be at $ 852 and was noted to be less than the mean value. With 95% confidence, the
average selling price for real estate properties in Australia was estimated to be within [$ 824200,
$ 942530].
Table 1: Descriptive Statistics for Price (in $’000)
886.58
29.66
852.00
811.00
324.95
0.43
0.22
-0.15
0.44
1569.00
192.00
1761.00
25 633.75
50 852.00
75 1087.25
Mean
Std. Error of Mean
Median
Mode
Std. Deviation
Skewness
Std. Error of Skewness
Kurtosis
Std. Error of Kurtosis
Range
Minimum
Maximum
Percentiles
Table 2: Confidence Interval of Average Selling Price of Properties
Lower Upper
886.58 0.06 29.32 824.20 942.53
Bias Std. Error
95% Confidence
Mean
Statistic
Bootstrapa

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The variable (Price) was plotted in a histogram and has been presented in Figure 1. The
normal line has also fitted the histogram. The variable was noted to follow Gaussian nature with
almost near zero skewness. The confirmatory tests was conducted using Shapiro-Wilk (W =
0.98, p = 0.12) and Kolmogorov-Smirnoff (S = 0.06, p = 0.20) tests. The null hypothesis failed to
get rejected at 5% level of significance, and it was concluded that the price of the real estate
properties was normally distributed (Corder, & Foreman, 2014).
Figure 1: Histogram for the Selling Price of Real Estate Properties
Table 3: Normality Check with Shapiro-Wilk and Kolmogorov-Smirnoff Tests
Statistic df Sig. Statistic df Sig.
Price 0.06 120.00 .200* 0.98 120.00 0.12
LotsizeSQ 0.23 120.00 0.00 0.86 120.00 0.00
Material 0.25 120.00 0.00 0.78 120.00 0.00
Condition 0.20 120.00 0.00 0.88 120.00 0.00
Kolmogorov-Smirnova Shapiro-Wilk
b) Lot Size
Lot size of the real estate properties (M = 1175.23 Sq.M, SD = 372.90 Sq.M) was noted
to be have a positive skewness (SKEW = 0.84). The median of lot sizes was identified to be at
980 square meters and was noted to be highly less than the mean value. With 95% confidence,
the average lot size for real estate properties in Australia was estimated to be within [1107.26,
1242.16] square meters.

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Table 4: Descriptive Statistics for Lot Size (Sq .M)
N Valid 120.00
1175.23
34.04
980.00
890.00
372.90
0.84
0.22
-0.56
0.44
1318.00
632.00
1950.00
25 910.00
50 980.00
75 1438.00
Minimum
Mean
Std. Error of Mean
Median
Mode
Std. Deviation
Maximum
Percentiles
Skewness
Std. Error of Skewness
Kurtosis
Std. Error of Kurtosis
Range
Table 5: Confidence Interval of Average Lot Size of Properties
Lower Upper
1175.23 -1.97 34.75 1107.26 1242.16
95% Confidence
Mean
Statistic
Bootstrapa
Bias Std. Error
The lot size was plotted in a box-plot and has been presented in Figure 2. The variable
was noted to be significantly positively skewed. The confirmatory tests was conducted using
Shapiro-Wilk (W = 0.86, p < 0.05) and Kolmogorov-Smirnoff (S = 0.23, p < 0.05) tests. The null
hypothesis got rejected at 5% level of significance, and it was concluded that lot sizes of the real
estate properties were not normally distributed.
Figure 2: Box Plot for Lot Size of the Properties