Comprehensive Analysis of House Prices in Kingfisher Bay, Melbourne

This report provides a comprehensive analysis of house prices in Kingfisher Bay, a fictional suburb within Melbourne, Australia. It examines various aspects including average and median house prices, the relationship between house prices and the condition of suburbs, and the impact of factors such as rental investments on house values. Statistical tests are conducted to determine average weekly rent, the age of houses, and potential future house price estimations. The analysis includes the use of bar plots and linear regression models to illustrate findings and determine key indicators influencing higher house prices. The report also addresses concerns raised by real estate agents and developers, and proposes future survey directions, offering valuable insights into the Kingfisher Bay real estate market.

Running head: BUSINESS ANALYSIS
Business Analysis
Name of the Student:
Name of the University:
Author’s note:

1BUSINESS ANALYSIS
Executive Summary:
The report discusses about five topics that are House prices in Kingfisher Bay, House prices
vs. condition/suburb, House prices vs. factors influencing house prices, concerns raised by
real estate agents and developers and future surveys. The average and middle value of house
prices of Kingfisher Bay are estimated here. The prices of houses with respect to conditions
of suburbs in Kingfisher Bay are summarised for presenting suburbs wise house prices. How
the variable “Rental investments” with good level are associated with house prices is
determined by linear regression model. The necessary test for finding average weekly rent
more than $600 is carried out along with the age of 75% of houses. In the future survey, we
are eager to estimate future house prices within $50,000 with the true proportion of house
prices 3%. The rental prices, house prices and rental investments according to the conditions
and suburbs of Australia are shown in the report. All the calculations of tests are carried out
assuming 5% possibility of rejection. You would be able to find our opinions regarding
analysed report of real estate sector with the approach of business purpose.
The data file of Kingfisher city have been structured for educational purpose. In the data file,
houses except flats and apartments are known as separate livings. The data of households
include twenty-three variables. Most of the variables such as Price, Rooms, Bedrooms and
Rental Return in percentage are numeric in nature. Some of the variables such as Material,
Style, Suburb or Heating are nominal in nature. Few variables as Condition or Street are
ordinal data variables. We are mainly focusing on house price, suburbs and condition factors
to estimate the outline of the Kingfisher Bay. Various types of statistical testing and assertion
testing are carried out in the calculation part of the report along with the appropriate bar plot
and linear regression model.

2BUSINESS ANALYSIS
Table of Contents
Introduction:...............................................................................................................................3
Discussion and Data Analysis:...................................................................................................3
House prices in Kingfisher Bay:............................................................................................3
House prices vs. Conditions of suburbs in Kingfisher Bay:..................................................4
House prices vs. Condition of Suburbs in Kingfisher Bay:...................................................6
Concerns developed by real estate agents and developers:....................................................7
Future Surveys:......................................................................................................................8
Conclusion:................................................................................................................................8

3BUSINESS ANALYSIS
Introduction:
The city Kingfisher Bay is a conjured city within greater Melbourne and does not look
like to any existing organisation or city. The city is consists of a number of various suburbs.
Kingfisher Bay was constructed in various stages with new emerging suburbs. It involves
some wealthy and some not so wealthy suburbs. The city is located on the bay. The city
expands many kilometres along the beautiful beaches of bay and several kilometres inland.
Almost sixty thousands people dwell in the suburbs of Kingfisher Bay.
Discussion and Data Analysis:
House prices in Kingfisher Bay:
The overall summary statistics of 120 house prices in Kingfisher Bay indicates that
average of the price of house is $886.58 and middle value of the prices is $852. The
difference of highest and lowest value of the price of houses is $1569 as the price of houses
varies from $ 637.25 to $1081.75.
The media articles focus on middle value of house prices and not the average. The cause
is that, measure of middle value is more effective when sample size is big and does not
involve outliers (the data that is not fitting according to the central tendencies of the
distribution). Middle value stays in the middle of the dataset after orderly arrangement. The
unfitted value of the central tendency does not also hamper the stability of Middle value. This
dataset does not include unfitted value and the sample size is small. Besides, the average
gives better approach of closeness of data values. Therefore, we must use the average for
appropriate summary measure in this dataset, as it is more proper and less inconsistent
measure of closeness of data values.

4BUSINESS ANALYSIS
The proper measure of the average house price for all houses in Kingfisher Bay is within
the interval of $828.43 to $944.72 with a significant level of validity.
The number of houses that sold for $1 million or more is 43. The proportion of such
houses is 0.36. The proportion varies between 0.27 and 0.44 with a significant level of
validity for the values of houses.
House prices vs. Conditions of suburbs in Kingfisher Bay:
Summary of conditions of houses: The frequency table and bar plot shows that most
of the houses of Kingfisher Bay are either “Good” (frequency = 42) or “Poor” (frequency =
40) in condition. These two types of conditions of houses are followed by “Excellent”
(frequency = 23). The lowest count of house condition is “Very poor” with frequency 15. The
heights of bars in the bar plot are adjusted as per numbers of houses.
Difference in means:
 We applied the testing procedure for examining equality of averages of levels of
conditions of the houses among the suburbs in Kingfisher Bay. Our pre-assumed
assertions are-
Basic assertion (H0): The averages of levels of conditions of households are equal for all
types of house conditions.
Alternative assertion (HA): There exists at least one inequality of averages of levels of
conditions of households for all types of house conditions.
The possibility of rejecting the basic assertion is 0.155998 that is greater than 0.05.
Therefore, we accept the basic assertion of equality of averages of levels of conditions with a
significant level of validity. We can say that the average levels of conditions of households
are equal for all types of conditions of houses.

5BUSINESS ANALYSIS
 We applied the testing procedure for examining the equality of average house prices
of all house conditions in Kingfisher Bay. The pre-assumed assertions are-
Basic assertion (H0): The averages of prices of conditions of households are equal for all
types of house conditions.
Alternative assertion (HA): There exists at least one inequality of averages of prices of
conditions of households for every type of house conditions.
The possibility of rejecting is 0.000186 that is lesser than 0.05. Therefore, we reject
the basic assertion of equality of averages of house prices of conditions of households with a
significant level of validity. We can say that the average level of prices of conditions of
households is equal for all types of house conditions.
 We applied the testing procedure for examining the equality of averages of house
prices of all house suburbs in Kingfisher Bay. The pre-assumed assertions are-
Basic assertion (H0): The averages of prices of conditions of households are equal for all
types of house suburbs.
Alternative assertion (HA): There exists at least one inequality of averages of prices of
households’ conditions for all types of suburbs.
The possibility of rejecting is 0 that is lesser than 0.05. Therefore, we reject the basic
assertion of equality of averages of house prices of households’ conditions with a significant
level of validity. We can say that the average levels of prices of all house suburbs are equal.
From the so far analyses, we can decide that levels of conditions of different suburbs
in Kingfisher Bay are equal. However, the prices of houses of different conditions and

6BUSINESS ANALYSIS
different suburbs are not equal to each other. From the completed analyses, we can determine
that suburb or condition has a bigger influence on prices of houses.
House prices vs. Condition of Suburbs in Kingfisher Bay:
Higher house prices have dependency on good rental investments:
We consider the house price as response or dependent variable and return of rent as
single predictor or independent variable.
In this problem the linear regression model is-
Price$000 = 1300.51898 -111.425027*RentalReturn.
Hence, only 16.31% variability of house prices could be described by return of rent.
The linear relationship of these two factors is negligible. The possibility of rejecting the
significance of validity is (0.0) that is less than 0.05. According to the slope of dependent
variable (a = -111.425027), we could state that RentalReturn is negatively related with
Price$400. Hence, we can draw the conclusion that the rental return is unable to estimate
house-prices. The fitted graph shows that the fitting is not also good.
We supposed that good rental investments are looking for higher house prices. Hence,
certainly our guess and concern of assumption of relevance of higher house prices with
respect to good rental investments is not valid. The higher house prices driven by suburb or
condition do not have a bigger impact on house prices.
Key Indicators of higher house prices:
The factors such as Age (-0.21782155), distance from buses (-0.02383229), distance from
shops (-0.08373382), Kitchen (-0.0560762) and RentalReturn (-0.4038396) are negatively

7BUSINESS ANALYSIS
correlated. This means, when the values of these factors increase, then the values of price
decrease.
The value of link of Price is moderately or highly positive with Rooms
(0.505469281362907), Areasqm (0.567769140342605), Street (0.722570047931952),
Storeys (0.565098454839622), Bedrooms (0.539744531398654), Bay Views
(0.676193864685365) and WeeklyRent$ (0.665590917485361). Hence, these are the major
factors for estimating prices of houses. These factors are the considerable indicators of higher
prices. This means, when the values of these factors increase, then the values of price
increase. These factors are the key indicators of the higher house prices.
Concerns developed by real estate agents and developers:
Weekly rent in Kingfisher Bay is at least $600
Suburb 1: According to the calculation, Suburb1 shows that the basic assertion of average of
house prices is less than $600 is accepted. Therefore, the assumption of weekly rent of
Kingfisher Bay at least $600 is false.
Suburb 2: According to the calculation, Suburb2 shows that the basic assertion of the
average of house price is less than $600 are accepted. Hence, the assumption of weekly rent
of Kingfisher Bay at least $600 is false.
Suburb 3: According to the calculation, Suburb3 indicates that the basic assumption of the
average of house price is less than $600 is accepted. Hence, the assumption of weekly rent of
Kingfisher Bay at least $600 is false. The average price is higher in case of Suburb3 of
Kingfisher Bay.
For all the three suburbs, the assumption of weekly rent in Kingfisher Bay of being at
least $600 is invalid.

8BUSINESS ANALYSIS
At least 75% of houses are 10 years old or more:
According to the possibility of rejection region in this sample proportional table, we
accept the basic assertion of proportional value less than 0.75. Hence, the assumption of age
of 75% of houses 10 years and older is false at a significant level of validity.
Future Surveys:
We are keen to compare house prices and rental availability. Specifically, the
estimated average house price is less than $50000 and the true proportion of vacant houses in
the market is within 3%.
The minimum sample size for calculating average is 163. The minimum sample size
for proportion is 51. The table “Numerical Variable” of known standard deviation is
considered for total size of the samples. With a high significant level of validity, the prices of
house lie in the interval of $828.44 and $944.72. The table “Categorical Variable” of
unknown proportional standard deviation shows the variation of prices of house of Suburb C
indicates that there is a high chance of validity of proportions lying between 27.25% and
44.41%. The table of “Numerical Variable” when measure of deviation is known shows that
measure of deviation are 244.717 and average of is 647.439 for the samples with sample size
41. The probability of rejection region shows that the assertion of mean house price less than
$600 is rejected with a significant level of validity. The table of “Categorical Variable” when
measure of deviation of proportion is unknown shows that among the sample size 120, we
found the proportion of sample as 78.33% with standard error 3.76%. Therefore, we reject the
basic assumption of average is less than 75% is rejected with a significant level of validity.
Conclusion:
We may decide that most of the houses of Kingfisher Bay have Condition “Good”.
The average prices of various Conditions and Suburbs are unequal. However, average Suburb

9BUSINESS ANALYSIS
levels in various Conditions have equality. The assumed assertion of average price is lesser
than equal to $600 for all the three suburbs. The assumed average and proportion table
indicates that the average house prices of all the suburbs is greater than or equal to 600 and
proportion of age of houses greater than 10 years is more than 75%. The inter-relation among
different estimators is described in this research analysis. You should not depend on rental
investment for estimating house prices. You would also be concerned about the fact that more
than 75% houses ages of the houses are older than 10 years.