Property management has become a development area in the recent past. It has been seen to evolve over the
years with radical changes in its structuring and management. Most property management agents are engaged in
residential, commercial, and real estate’s including apartments and detached houses (Lees, 2001).
In management, property manager are able to run business from management of large amount of businesses and
apartments. Therefore, creating a need for firms to evaluate most crucial factors that they should ensure are
looked into for increased profitability. It has been stipulated, that possible factors could include; the lot size,
number of rooms, number of bedrooms, and type of parking and architectural style. However, there has not
been a single literature that has looked into the question carefully to help property managers locate their
business in areas of business growth (Lees, 2001). In addition, little has been done in assessment of the most
critical factors which lay bases to the current study. Therefore, the current study will be undertaken to fulfil the
1. To compare the value of property in East Meadow and Farmingdale.
2. To find out whether there is an association between architectural style of property and geographical
3. To find out whether there is a relationship between lot size of property and number of rooms.
To achieve the first objective, the analysis will be conducted through descriptive statistics. First histogram for
both geographical locations will be presented, after which an independent t-test will be conducted to assess
whether there exists any significant difference in value between the two geographical regions.
Objective 2 will be captured through a first simple bar graph which will present the distribution of architectural
styles. Then a cluster bar which cross tabulations will be presented to assess the associations between
geography and architecture. Finally, a chi-square test will be assessed to assess significant difference in the
To achieve the third objective correlations will be run to assess association between lot size and the number of
rooms. Further a regression will be run to assess the effect of the lot size on the number of room an apartment
2.0: Objective 1: comparing value in East Meadow and Farmingdale.
2.1: Descriptive statistics for appraisal value in East Meadow and Farmingdale
Variable Number of
East Meadow 59 213.00 37.62 155 310
Farmingdale 50 191.8 30.29 115 305
Looking at the means, it is possible to tell that East Meadow has a higher value compared to Farmingdale. The
mean vale for property in East Meadow is $213,000 while the mean vale of property in Farmingdale is
$191,800. From the analysis, out of the 300 responses, 59 of properties came from East Meadow, and 50 from
Farmingdale. This composed of 19.67% and 50% of the total sample respectively. The minimum value for
property in East Meadow is $155,000 and the maximum value is $310,000. On the other hand, the minimum
value of property in Farmingdale is $115,000 and the maximum value is $305,000. This is an indication that on
average people in East Meadow afford to pay for apartments worth $213,000, while those in Farmingdale
afford to pay for apartments worth $191,800.
Making use of a distributional plot, the histogram below shows that the value of property in different regions
varies. Looking at the plot, value in East Meadow is highly concentrated at around 150,000-200,000, which the
highest frequency of 12 being below $200,000. On the other hand, Farmingdale has most of its values lie
between 150,000-200,000, with the highest frequency of 19, being below $200,000 and close to the mean value.
This is an indication that most people in East Meadow, prefer paying a value less than the mean of $213,000.
On the other hand, people in Farmingdale prefer to pay a price around the mean vale of property in the area.
People in East Meadow do not prefer paying for apartment’s worth below $150,000 as they are considered of
low quality. This is a similar observation of people in Farmingdale area. The lowest frequency equals 1 for East
Meadow which occurs at $155,000, while the lowest for Farmingdale is 1 which occurs at $115,000. This price
is not taken by many as is considered a very low price thus associated with low quality apartments. On the other
hand East Meadow has a low frequency for property valued above $300,000, with 1 at $310,000. At
Farmingdale property worth above $250,000 is not highly chosen with a frequency of 2. This values are seen as
extremely expensive for people and thus they are not taken up. They are seen to exceed the average value
people in both places can afford. But though it should be noted that even though only a few take the low price
apartments and the very high price apartments, the high price one will get the best as they are able to pay the
price, and the low people get the low quality as they are not able to pay the average price.
appraisal value (thousand dollars)
Graphs by geographic location
histogram for appraised vlaues by geography
It should be well noted that only a few people are able to afford the high price apartments but they go for them
as they are able to pay the price. Though generally, property in East Meadow is highly valued compared to
2.2: Difference between mean appraisal in East Meadow and Farmingdale
From, the analysis, we have been able to spot that prices in different geographical regions differ. It is however,
important to make a hypothetical test to assert, that the value difference is statistical. And thus areas with a
higher mean are statistically highly valued compared to those with lower mean. This engaged an independent t-
test. As shown in the table below, the mean value of property in East Meadow is $213,010,000, and that in
Farmingdale is $191,810,00.
N Mean Std.
apparised value in
East Meadow 59 213.01 37.628 4.899
Farmingdale 50 191.81 30.295 4.284
Ho: µ E = µ F
Ha: µ E ≠ µ F
ɑ= 0.1, p-value (from test) = 0.002
Decision: reject H o
The independent sample test as shown below indicate that there is a significant difference in the mean value of
apartments in East Meadow and Farmingdale. We are 95% confident that the variance value in the two area are
Independent Samples Test
t-test for Equality of Means
F Sig. T df Sig.
Interval of the
5.919 .017 3.2
107 .002 21.201 6.625 8.068 34.333
.002 21.201 6.508 8.299 34.102
The results showed, that there existed a statistical difference in the mean appraisal value between and within the
geographical locations. As thus we can conclude, that East Meadow, has a statistically high appraisal value
compared to Farmingdale. The test indicates that there is also a statistical difference in the variance. This means
that the value deviations are different in the different regions. As thus the variance in East Meadow is
significantly higher than that of Farmingdale.
From the analysis, we can be able to conclude that there is enough statistical evidence to say that the value of
property in East Meadow is not the same as that in Farmingdale. In fact it higher than the property value at
Farmingdale. This is also an indication that income levels in East Meadow is higher than in Farmingdale.
Therefore, property management agencies would benefit as more property will be raised in East Meadow to
capture the high income earner, thus have a positive impact on their profits. On the other hand, in Farmingdale
that appraisal value is lower and thus less demand for property which will lead to less property management
firms. Therefore, the firm should focus on Farmingdale which is less attractive to most firms and use a low
price high volume strategy thus gain profits.
3: Objective 2: To find out whether there is an association between architectural style of property and
3.1: Graphical presentation of architectural styles
It was important to first look at the distribution of architectural styles in the area. People have different
preferences for different designs. The figure below indicates that Ranch has the highest count with 103,
followed by Cape with93, Colonial with38, Spliot level with37, and last is expanded ranch with 29.
3.2: Graphical presentation of architectural design in different geographical locations
To assess the association between geography and architectural style there is need for a cluster bar chart
The results from the figure above indicate that expanded Ranch is the least preferred architectural style in
different geographical locations. The cape style and ranch style are highly preferred, which cape highly
preferred in Levittown with a frequency of 44 as shown in the table below. On the other hand ranch is highly
preferred in Iaslip with a frequency of 33. In East Meadow, the most preferred style with a frequency of 14 is
Spliot level. And in Farmingdale, they highly prefer use of Ranch style.
geographic location * architectural style for the house Crosstabulation
architectural style for the house Total
24 1 6 14 14 59
13 1 6 17 13 50
Levittown 44 8 5 22 2 81
Islip 10 11 14 33 4 72
2 8 7 17 4 38
Total 93 29 38 103 37 300
3.3: Chi-square test of association between architectural style and geographical location
The association show that geography and style are different. However, it is important to test this hypothesis
thus necessitating the use of a chi-square test. From the table below, the person chi-square value is 82.37 which
is significant at 1%. This is an indication that there is significant difference in style applied in different
H 0 : no association of geography and architectural style
H a : there is association of geography and architectural style
ɑ= 0.05, p= 0.000
Decision: reject H 0
Value df Asymp.
Pearson Chi-Square 82.366 a 16 .000
Likelihood Ratio 88.395 16 .000
.899 1 .343
N of Valid Cases 300
a. 4 cells (16.0%) have expected count less than 5. The
minimum expected count is 3.67.
From the analysis we thus conclude that there is association between architectural style and geographical
location. The architectural design helps look at space, environment, and design. The geographical position
looks into the position of the apartment. Therefore, it is clear that in choice of an apartment one will look at its
position, continue to looking at its size, design, outlook, and the environment which are important consideration
to the value of an apartment.
4: Objective 3: to find out whether there is a relationship between lot size of property and number of
4.1: Correlation analysis
To assess the association, the correlation measure the strength of the association between variables. The
analysis as shown in the table below show existence of strong relationship
H 0 : person R= 0
H a : Pearson R≠ 0
ɑ = 0.05, p=0.344
Decision: fail to reject H0. Thus conclude that there is weak linear association between the two variables.
Std. Error a
.055 .057 .948 .344 c
.046 .060 .792 .429 c
N of Valid Cases 300
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
c. Based on normal approximation.
4.2: Linear relationship between lot size and number of rooms
It is thus important to assess the relationship. Hence necessitating the use of a linear regression model.
Variables Entered/Removed a
lot size in
a. Dependent Variable: number of room
b. All requested variables entered.
As shown in the table above, number of rooms becomes the dependent variable while the lot size becomes the
1 .122 a .015 .011 1.314
a. Predictors: (Constant), lot size in square feets
As shown in the table above, the mode is able to explain 1.1% variability in number of rooms. And thus lot size
can be able to explain 1.1% of the variability in number of rooms.
Model Sum of
7.720 1 7.720 4.473 .035 b
Residual 514.267 298 1.726
Total 521.987 299
a. Dependent Variable: number of room
b. Predictors: (Constant), lot size in square feets
The ANOVA table shows that the overall model fitness is good at 5% level of significance. And thus the model
is bale to fit the data and can be used to explain the relationship between lot size and number of rooms.
B Std. Error Beta
(Constant) 6.712 .159 42.343 .000
lot size in square
.031 .015 .122 2.115 .035
a. Dependent Variable: number of room
Finally, the coefficient is significant at 5%. This is an indication that lot size influence the number of rooms in
an apartment. The coefficient indicate that a unit feet increase in the lot size, increases the number of rooms by
3.1%. This is because the coefficient sign is positive indicating a positive relationship between the variables.
Constant = 6.712
Y= a + bx
Y= 6.712 + 0.031x
R= beta= 0.122
An association that is below 50% indicates a weak relationship. In this case we have a weak positive
relationship between lot size and number of rooms. This means that there is need to add more variable to the
model to be able to predict factors influencing the number of rooms more appropriately.
The study was conducted with a random sample of 300. The results indicated that the average value of property
in East Meadow is $213,000, and the value in Farmingdale is $191,800. The values were seen to be
significantly different form each other and that of East Meadow was significantly higher. It was realised that
most people preferred the Ranch style, followed by case, and least preferred the expanded style.
From the analysis it is clear that geography is an important part of determining the value of an apartment.
Different locations have significantly different values and thus management firms need to get to area that have
lesser competition. In addition, it is important to note that geography is highly associated to architectural style
and people will look at the position of an apartment as well as its environment to assess the value. In addition,
lot size influences the number of rooms in an apartment but portray a weak positive association.
6: Limitations and suggestions
Thus the current analysis recommend for further analysis to the issues to assess other factors that may have an
influence on the value of an apartment. There is need to get more factors into the model for factors influencing
number of room since lot size is not the only factor. In addition, the study was conducted with a sample of 300
which is small compared to the coverage. Thus recommended for further research making use of a bigger
sample to reduce bias.
Lees, L. (2001). Towards a critical geography of architecture: