Data Zone’s Housing Market Analysis for Whitehorse

The memo presents an analysis of recent real estate market data for Whitehorse. It describes the database used, sample size, and categorization of houses based on their conditions, suburbs, and rental status. The analysis covers house prices, conditions, affordability, rental properties, and appropriate sample size. The results provide insights for decision making in future market analysis.

Memorandum: Data Zone’s Housing Market Analysis
Student’s name:
Student’s ID:
Institution:

Memorandum
Date: 20th January 2017
To: Zoe Zhou, Chief Data Analyst
From: Sandy Stedwell, Research and Analysis Department
Subject: Analysis of Whitehorse Market Data
Dear Zoe,
As instructed, the following memo will be able to open up on some of the issues at hand. The
results, will therefore play a key part in decision making now and in future market analysis. An
analysis was carried out of the recent real estate market data for Whitehorse as requested. Before
the presentation of the results obtained, it will be of great importance to provide a description of
the database used. The data on Whitehorse data provided contained twenty-four fields. The
fields are HouseNo, Rooms, House Price, Age, HouseAreaSqm, LandSizeSqm, Material, Street,
Storeys, ToTrainKm, ToBusKm, ToShopsKm, Bedrooms, Bathrooms, Style, Kitchen,
MountainViews, Heating, WeeklyRent, AirCon, RentalReturn percent, Suburb, Condition, and
Rental Status. The sample size of the data used was 120, that is, 120 houses in Whitehorse were
used in the market data. The houses in Whitehorse were priced in Australian dollars with
different characteristics such as the number of rooms which can be considered as main in the
house, the area of a block of land in squared meters, the area of the house in squared meters and
the age of the house in years. The houses were made of building materials which ranged from
timber to veneer to brick. The houses also had varying distances from either the train station, the
bus stop, or the shopping center. These distances were measured in terms of kilometers. The
houses had a varying number of stores or levels in the house with varying number of bedrooms
and a varying number of bathrooms. A sense of style could also be observed among the houses
with some of them being traditional while the others were non-traditional. The style was also a
component of the kitchens as some of them had the older style while the others were modern.
Depending on the house, some of the houses had installed a central or other heating system while
others had not. This also applied to the presence of an installed air conditioning in the houses.
The real agency also had evaluated the street appeal at the proximity of the house giving a rating
of 0 for the lowest appeal up to a rating of 10 to the highest appeal. The view of Mt Dandenong
was also a factor with evaluation rating the proportion of views of the mountain. A full view was
rated at 1 while a nil view was rated at 0. Depending on the proportion, in between values were
also given. The houses were also evaluated with regards to the suburbs they were in. these
suburbs in Whitehorse were Box Hill, Mont Albert, and Surry Hills suburbs. The weekly rent in
dollars, whether the actual or estimated was estimated. In this respect, the annual rate of return
forms the rental income as a percentage was also obtained. The condition of the houses, in
general, was also determined with the option being in a very poor, poor, good or in excellent
condition. The rental status of the house was also obtained with houses being either vacant
(available for rent), rented (currently rented) or owned (occupied by owner). These data were
then placed into their respective field and the obtained database was used for analysis.
Q1. An Overall View of House Prices

It is evident that the data was collected from 120 houses in Whitehorse. On average, house prices
in Whitehorse is $889.55. The spread of house prices was $326.15 on each side of the average.
The highest house price in Whitehorse was $1,731 while the lowest was $224. All in all, we can
say with a 95 percent confidence that the mean house price in Whitehorse falls between $831.20
and $947.90.
Q2. House Prices vs Condition
The houses in Whitehorse were categorized into four in accordance with their conditions. The
conditions are very poor, poor, good and excellent. From these, it is seen that the majority of the
houses in Whitehorse are in good conditions. This is represented by 35 percent of the houses in
Whitehorse sample data collected. Consequently, houses in poor conditions came in second with
a representation of 33 percent of houses in the Whitehorse data collected. A small number of
houses were deemed to be in excellent conditions or being in very poor conditions. This is seen
by the house representation of 19 percent of houses which are in excellent conditions while 13
percent of the houses are deemed to be in very poor conditions.
The houses were indeed priced differently based on their conditions. The houses in excellent
conditions were highly priced. On average, they had the highest average price of $1,137. The
houses in good conditions were priced lower than the houses in the excellent conditions. On
average, the houses in good conditions were priced at $871.14. Indeed, with a deterioration in the
conditions of the house, it was seen that the house prices did decreases. Houses which are in poor
conditions were priced lower than the house in good conditions. Thus, they had an average mean
price of $813.35. The houses in very poor condition were the lowest priced among the four
conditions of categorizing the houses. Hence, the houses in very poor conditions had the lowest
average price of $764.27.
The area of Whitehorse was categorized into three suburbs. The suburbs were Box Hill, Mont
Albert, and Surry Hills. The houses in the three suburbs were then categorized based on their
conditions. That is, whether they were in very poor, in poor, in good or in excellent conditions.
With this in mind, it was established whether the three suburbs had different conditions for their
houses. It was established that with regards to conditions, there was no evidence that proves
there was a significant difference in the condition of houses among the three suburbs. However,
based on graphical displays, it was seen that in Box Hill suburb, most of the houses are in good
conditions. Similar observations can be made for Surry Hills suburb where most of the houses
are in good conditions. However, in Mont Albert suburb the majority of the houses are in poor
conditions.
Q3. House Affordability
There is a numerous number of newspaper articles which are focusing on house affordability in
Melbourne (Abelson & Chung, 2005). With this regards, in the whole of Whitehorse the
proportion of houses which are worth $1 million or more was obtained. It was estimated that in
Whitehorse 35 percent of the houses are worth indeed $1 million or more.
On the other hand, the proportion of houses in Whitehorse wholly which are valued at less than
$600,000 was also obtained. The results were that it was estimated that 21 percent of houses
across Whitehorse were valued at $600,000.

It was hypothesized that the house prices differ by suburbs in the whole of Whitehorse. This was
proved true by the fact that the house prices differed by suburb, a difference that was significant.
Hence, it was seen that the prices of houses in Surry Hills had the highest house prices of $1,064
on average. The suburbs of Mont Albert were ranked second based on the prices of houses with a
mean average of $843. The lowest ranked suburb based on house prices was Box Hill. Box Hill
had an average house price of $767.
Q4. House Prices vs Suburb
An article was published last month by a local newspaper which asserted that the mean auction
price of all houses in Melbourne currently exceed $750,000. But how do these house prices
relate with the house prices in Whitehorse suburbs with this prediction? It was found out that the
average house prices in Whitehouse did indeed actually exceed $750,000. Thus, it is clear that
the average house price movement in the Whitehorse suburbs do actually follow the forecast
house prices. Hence, when the house prices in Melbourne rise, a similar observation will also be
seen in Whitehorse.
Q5. Rental Conditions
At the moment, there is concern regarding the housing affordability and the lack of rental
properties available not only right across Melbourne but also in Whitehorse (Jud & Winkler,
2002). The areas of Whitehorse is not an exemption. A REIV senior manager has claimed that
the proportion of rental properties which were unoccupied had plummeted below 7 percent at a
recent public meeting (Collister & Stowe, 2013). Nonetheless, this claim does not board for all of
Whitehorse. It was found out that indeed, the rental properties proportion that are vacant in
Whitehorse did not drop below 7 percent.
Moreover, the Senior Manager ascertained that the mean weekly rent had now increased to over
$570. In addition, this assertion was not applicable to all of Whitehorse. In Whitehorse, the mean
weekly rent had indeed not risen to over $570.
Q6. Appropriate Sample Size
The concern of the sample of 120 auctions reported on in Whitehorse regarding it being too
small to provide results that can be deemed accurate thereby seeming hardly enough data has
also been noted. The sample of 120 auctions reported on in Whitehorse is indeed too small to
offer a precise result. For the future study to be undertaken next year, estimating the proportion
of houses worth over $1 million to within a level of confidence that is considered as high will
require a sample size of 385. Thus, selecting a random sample of 385 from a population and
determining that 50 percent of the houses in Whitehorse are worth over $1 million. The sample
size of 385 would lead to a 95 percent confidence that between 45 percent and 55 percent of the
houses in Whitehorse are indeed worth over $1 million.
On the other hand, to accurately approximate the average weekly rental income to within $50,
the number of houses that will be needed in the sample to be included in survey to be carried out
next year to satisfy the requirement will still need to be maintained at 385. Thus, to estimate both
requirements, a sample size of 385 will be needed.
Having a large sample will make it possible to generalize the results to all of Melbourne. The
advantages of having a large sample size if the apparent advantage of providing more data for to

work with for the researchers (Berenson et al., 2012). Moreover, a larger sample size ensures that
the mean of the data is more precise making it more easily positive to pinpoint outliers (Berenson
et al., 2012). Hence it will be possible to generalize the results to all of Melbourne and therefore
making it possible to save a lot of work of duplicating the study in other suburbs.
Regards,
Sandy.

Reference:
Abelson, P. and Chung, D., 2005. The real story of housing prices in Australia from 1970 to
2003. Australian Economic Review, 38(3), pp.265-281.
Berenson, M., Levine, D., Szabat, K. A., & Krehbiel, T. C. 2012. Basic business statistics:
Concepts and applications. Pearson higher education AU.
Collister, L. and Stowe, B., 2013. Doorway: The way in to housing. Parity, 26(5), p.32.
Jud, G.D. and Winkler, D.T., 2002. The dynamics of metropolitan housing prices. The journal of
real estate research, 23(1/2), pp.29-46.