Kingfisher Bay Real Estate: Price and Rent Analysis Report

This report provides a detailed analysis of the real estate market in Kingfisher Bay, Melbourne, based on a sample of 120 properties. It addresses key questions posed by the research director regarding property prices, rental rates, and market conditions. The analysis includes a determination of median property prices, an examination of significant differences between property characteristics (condition, suburban type, and price), and an assessment of the correlation between house prices and various factors such as street appeal and bay views. The report also investigates the accuracy of claims regarding average rental prices and vacancy rates in the area, utilizing statistical tools like z-tests and correlation analysis to draw conclusions and provide insights into the Kingfisher Bay property market. Desklib provides similar solved assignments for students.

Table of Contents
Executive Summary.....................................................................................................................................2
Body of the report.......................................................................................................................................3
Question 1 – Median prices is the average prices....................................................................................3
Question 2 - Significant differences of the house....................................................................................3
Question 3 - To measure the degree of association between the house prices and other key variables....4
Question 4 – Rent and age of the household............................................................................................5
Question 5 – Average prices and Vacancy rate........................................................................................6
Conclusion...................................................................................................................................................6
References...................................................................................................................................................6

Executive Summary
The main aspect of this report is to perform a detailed analysis on the information which is
collected by the manager of research wing of REIV, the information is related to the various
factors like price of the house, conditions, bay area etc of Kingfisher bay area in Melbourne,
Australia. The manager of real estate research institute is concerned in understanding the price
movements of the properties in the Kingfisher bay area, there was a conception that the property
located in the area is expensive or the rents are always high, the manager is interested to
understand the hypothesis. In this conjuncture the manager has assigned the research team to
collate sample details from the bay area, the team has collected details of nearly 120 properties
and the details are mainly attributed to the selling price of the houses, lot size which is measured
in square metres, number of storey or levels, proportion of bay view from the property, type of
suburban etc. These data are analysed using various statistical tools and models based on the
questions and hypothesis set by the manager of the research institute. The purpose of this report
will be dependent on the issues and the questions which is raised by the Director of the research
institute on the questions and concerned rose in the area. The research director is of the thought
that the Kingfisher area is considered as the exclusive area with high prices in the market and
also the rental prices is also high in these areas. But the council members and the residents of
that area feels tha such aspects are false and due to this the director has taken up a full fledged
analysis based on the data and there are serious of questions which are posted by the director.
Hannah Zhou is the director and post 5 important questions which will be the base of preparing
the research work, this is involved in stating the median price of the house, they are also
interested in understanding the significant differences among the 3 key variables like the prices
of the houses, conditions of the house and the type of suburban. The next research question is to
find the degree of association among the prices and other key factors which contribute for
increase in the prices. The director is also interested to know that the rental prices in the area is at
an average rate of $600, the vacant properties in the locality is around 3% of the total households
in the area. So, these questions are addressed and a detailed interpretation is given based on th
analysis made from the data .

Body of the report
Question 1 – Median prices is the average prices
The director posted the first question with confusion that the average prices of the properties
which is stated in the newspaper are related to the average (mean) values, but in the news paper
they have stated that the prices are of median. However, the mean values and the median values
are entirely different. The average price is considered by adding all the values in the data and
then dividing the sum by the total number, but the median value is considered as the middle
value of the entire data set after arranging them in the ascending order, this shows that half of the
values will be above the median value and another half will be below the median values, the
computation of these values will take into account all the values presented in the data collection.
(Witte, 2010).
The median value is stated as the total set of data which lies half of the values above them and
another half are lying below the median values, so it is usually considered as the best measure to
understand the average prices, specifically the real estate properties. Based on the computation
the average prices is computed as $886.58 (in ‘000) and the mode value is $811.00 (in ‘000),
the mode is commonly stated as the number which occurs ore often in the data set. However, the
median value of the data collected based on 120 properties is stated to be $852.00 (in ‘000).
Therefore, it can be concluded that the prices which is stated in the newspaper of median number
is the average price and it can be stated that the median price is considered as the best measure
while measuring the average prices for the proporty. Moreover, it is usually stated that the
median values is stated to be the easiest measure, could be understood and widely accepted
measure as it does not get affected by many outliers.
Question 2 - Significant differences of the house
The next key question posted by the director to the research analyst is to measure and check
whethere there is any significant differences among the variables like the conditions of the
household, type of suburban in the Kingfisher bay area and the selling prices of the household.
Furthermore, the director is interested to know the conditions of the household in the bay area, so

it is stated that nearly 12% of the houses were in a very poor status, 33% of the house hold is at
poor nature, 35% of the household, which is the maximum of the 120 samples is having good
houehold conditions and the other 19% is having excellent conditions.
In order to understand and test if there are any significant differences among the variables, the
researcher intends to apply z test for this. It should be noted that the z test is one of the key
statistical test which is used to measure if the means of the population of two variables are
different, one of the key advantage of using this measure is that the test assumes that the data is
normally distributed and the other measures like standard deviation needs to be known before
computing the z test.
The first aspect is to test the significant differences between the type of suburban and the nature
and conditions of the homes in the area, while applying the z test it is noted that the p value is at
0.000, which is low than the 5% level of significance so the researcher needs to state that there
exist a significant difference between the type of suburban and the nature and conditions of the
homes in the area.
The next test is to measure if there is any significant differences between the prices of the houses
in the area and the type of suburban, while applying the z test it is noted that the p value is at
0.000, which is low than the 5% level of significance so the researcher needs to state that there
exist a significant difference between the prices of the houses in the area and the type of
suburban.
The last test is to measure if there is any significant differences between the prices of the houses
in the area and the conditions of the household, while applying the z test it is noted that the p
value is at 0.000, which is low than the 5% level of significance so the researcher needs to state
that there exist a significant difference between the prices of the houses in the area and the
conditions of the household..
Question 3 - To measure the degree of association between the house prices and other key
variables
The third part of the question which the director has posted is to understand the relationship
between the variables and the prices of the houses in the Kingfisher bay area. There are different

variables which have been considered while collating the data for the analysis. For this purpose,
the researcher wll use correlation analysis, Correlation analysis is a statistical analysis method
used to test performance for two consecutive variables in numerical terms (eg length and
weight). ESS and type of analysis are useful if a researcher wants to know if there are variables
among the variables. It is often misunderstood that the correlation analysis determines the cause
and effect. However, this is not the case because other variables that are not part of the research
can affect the results. If the relationship between the two variables means that if there is a
variable periodic change, others change regularly. The correlation between the Pearson product
moment and -1 to +1 correlation indicates the strongest possible positive correlation and -1
indicates the strongest negative correlation. Therefore, the higher the coefficient of one or more
numbers, the greater is the correlation between the data they represent. In this scale, 0 shows no
correlation, so the values closer to zero show a weaker / weaker correlation of almost + 1 / -1.
(Freedman, 2010). The most common correlation coefficient is the Pearson correlation
coefficient. It is used to test linear relationships between data. Depending on the type of data you
are using, you can find others. For example, the Goodman and Kruskal lambda coefficient are
quite common factors. The correlation factor is a way to assign a relationship. The correlation
coefficient is between -1 and 1. "0" means that there is no link between variables, while -1 or 1
means there is a perfect positive or positive correlation.
Based on the analsysis of the data it is noted that the correlation betwee the prices and the street
is stated to be 0.72, which is a high positive correlation, this shows that the street appeal is
considered to be the key variable in deciding the value of the houses, the next key variable is the
extent of bay view, better is the bay view higher is the selling price of the household, the
correlation between the prices of the houses and the bay view is 0.68. Therefore, these variables
possess as significant impact on the prices of the household, so the director of the institute must
consider these aspects in understanding the price differences in the household.
Question 4 – Rent and age of the household
The next question which the director needs to understand is the weekly rents in the suburban
area, there is a opinion that all the households in the Kingfisher area is having a average rent of
$600, in order to test this the average rents of all the suburbans are computed. From the analysis

it is identified that the overall average rent of all the suburban area is above $600, whereas the
weekly average rent in the 1st suburban area is at $577, whereas the 2nd suburban has a average
weekly rent of $588 and the 3rd suburban area is at $647. So, only the 3rd suburban area has the
weekly average rent is more than $600 whereas the other 2 suburban areas have the weekly
average rent of below $600. Also, the director is of the opinion that nealry 75% of the properties
in the bay area is more than 10 years old, from the data collated it is identied that more than 90
properties are more than 10 years old, so it is more than 75% of the total properties, therefore the
statement made by the director is correct.
Question 5 – Average prices and Vacancy rate
The average prices of the houses in the bay area is more than $50,000 therefore the statement
made by the director is correct, also in the last part on the vacancy houses, the estimated rate is
nearly 3%, however from the data collated there are nearly 13 properties in the samples are
vacant, since the total number of properties chosen is 120, the vacancy is nearly 10.5%, therefore
this statement is also correct
Conclusion
Based on the overall analysis it is identified that the best measure to state the average prices of
the houses in the area is to use the median price, this is considered to be the better when
compared with the average prices, furthermore there is a major differences among the variables
like the conditions and the area towards the prices charged in the area, the relationship between
the street factor and the bay view possess a high positive correlation towards the price. Also,
only the 3rd suburban area has the weekly average rate of more than $600 and other areas have
rental of less than $600. Lastlt, the vacancy rate is more than 10.5% which means that more
properties are vacant in the area.
References
1. Freedman, David (2010). Statistics. 4th Edition. Cengage Publishing
2. Sarah Boslaugh (2012). Statistics in a Nutshell. Cengage Publishing
3. Sincich T. Terry (2012). Statistics. 12th Edition.
4. Witte S. Robert, (2010). Statistics. 5th Edition. McGraw Hill

5. Triola (2014). Essentials of Statistics. 5th Edition. McGraw Hill