Melbourne House and Rental Data Analysis: MIS770 Assignment 2 Report

This report presents a data analysis of Kingfisher Bay's house and rental data, focusing on price trends, suburb comparisons, and potential for property subdivision. The analysis reveals that house prices are influenced by factors such as the condition of the house, weekly rent, and house area. Key findings include the median house price range, correlations between variables, and the acceptance or rejection of claims made by senior managers regarding rental properties and average selling prices. The report also investigates the relationship between different house sale results to optimize survey efforts. The study concludes by highlighting the factors driving house prices and suggesting strategies for future surveys, such as focusing on specific result combinations to save time and resources. The analysis uses statistical methods to draw conclusions and inform decision-making in the context of the Melbourne housing market. The report is designed to meet the requirements of the MIS770 course at the Faculty of Business and Law, assessing critical thinking and data manipulation skills.

Report 1
Report on Kingfisher Bay’s House and Rental Data
Objective: Data Analysis of Kingfisher Bay’s House and Rental Data.
Summary:
This is an attempt to know how the Kingfisher bay’s (Melbourne’s) house price are
increasing and how more suburb hove have a median house price. So, in the first part of the
Project Question, we cover the general exploratory analysis of renal data. In which we found
that major proportion of house based on house price is coming closer to Median, we found
that there is no correlation between different kind of suburb, and housing price is increasing
with increase in quality of house and housing price is depend on weekly rent.
In the second part of report question, contain the specialized data analysis of Melbourne City
of Kingfisher bay. In this analysis we found that 55 houses are going for subdivision and we
are accepting the claim of senior manager regarding the section of the properties rented which
were not occupied at the time (reduced to less than 25%) and we are rejecting the claim of the
mean price of bay side house which are exceeding $825K.
Again, we found that there is relation between Pair of Results (Passed In, Sold before the
Auction), (Passed in - Vendor Bid, Sold before the Auction) and (Sold during the Auction,
Sold Prior To Auction) Result so we can reduce our survey time.
Please find the answers of the given questions.
Part 1
Answer 1:
Summary of Housing Price
 According to Data Set (1). Average Price of House is 886.575.

Report 2
 The spread of house price from the mean is 324.9466.
 Median housing price is 852.
 The tail or we can say that flatness of Housing price distribution is -0.1477 or Plato-
type.
 Frequency distribution is slightly positive skewed.
 Range of the House price is 1569.
 Minimum housing price is 192.
 Maximum house price is 1761.
 Total sum of housing price is 106389 in Thousand.
According to frequency distribution of house prices from Data Set (1), we found that House
price is not following the symmetry nature. Distribution of house prices is slightly positive
skewed and mean of positively skewed data will be greater than the median. Therefore, the
focus of the media articles is on the median prices of the houses and not particularly in the
average.
Answer 2:
According to Data Set (1) we do the exploratory analysis of variation between 1, 2 and 3
Suburb and found that there is significant difference between In Suburb. It Means Housing
mean of these three suburbs is not equal.
Answer 3:
According to Data Set (1), House prices are increasing with increase in Condition of House.
If the Condition or Quality of House is Excellent then price of the house will be very high
and if condition of house is very poor then price will be very low.
The hierarchy of Housing price is like this.

Report 3
House prices of Condition four >Condition three >Condition two >Condition one
Yes, there appear conditional variations in the suburbs. Major proportion of house with
almost equal proportion of suburbs is coming under Poor and Good Condition.
It is analysing that the proportion of suburb 1 and 2 is low in very poor and excellent
condition. And proportion suburb 3 is equal in all Condition.
Answer 4:
According to analysis of Correlation proportion, correlation ratio of House price and
weekly rent is 67%, correlation ratio between House area and House price is 57% and
correlation between room and House price is 50%.
Hence House price is more dependent on weekly rent, House area and Room in House.
Weekly rent having a stronger influence on house prices and Land Size has the least
influence on house prices.
Part 2:
Answer 5:
House will be going for subdivision when the size of the land is at a minimum of 1000m2 or
above it.
So, there are only 55 House whose land size is greater than or equal to 1000m2 and 46%
proportion of the total number of houses in Kingfisher bay are appropriate for partitioning.
And the approximate mean land size in the entire Kingfisher bay is 1175.225m2.

Report 4
Answer 6:
According to Hypothesis testing of proportion of rental properties we have found that
proportion of rental properties is 4.17% and we are accepting the senior manager’s claim
that the section of properties rented which were not occupied had fallen below 25%.
Additionally, according to Hypothesis testing of average selling price of house we are
rejecting the claim that the mean price of the houses at the bay side had not gone above
$825K (that is, bay side houses refer to the houses in the suburbs and cities that are found
around the bay in Melbourne).
Answer 7:
Only 46% for house of land size 1000m2 0% of house coming under $20K.
Hence only 54% of house or 65 House are required to be incorporated in the survey that will
be conducted next year in attempt to realize the two requirements.
Results of all Melbourne is subdivided in 5 Part
 Passed In
 Passed In - Vendor Bid
 Sold After Auction
 Sold At Auction
 Sold Prior To Auction
Yes, the results obtained can be used to infer to Melbourne in general.
According to data analysis of housing price and Result of House of Melbourne, we found
that there is no significant relation between all five different result .but if we looked

Report 5
pairwise relation between the Result then we found that There is relation between (Passed
In, Sold Prior To Auction), (Passed In - Vendor Bid, Sold Prior To Auction) and (Sold
At Auction, Sold Prior To Auction).
So, we can save lot of work when we exclude any one Result between these Pair of result.
Conclusion:
Throughout the analysis of Housing price of Melbourne city of Kingfisher bay Data. We
found that major proportion of House price lies from $652K to $882K (Median). Price of
these houses is depending on Quality (condition) of house and average selling price of house
has not exceeded $825K. And approx. 68% of house is coming in Condition 2 and Condition
3 and Housing price is 67% correlated weekly rent and 57% House Area so we can increase
housing price when we allow the customer who is able to pay weekly rent.
For next year survey we can save lot work when we chose any one Result between this Pair.
 Passed In and Sold before Auction.
 Passed In - Vendor Bid and Sold before the Auction.
 Sold At Auction, Sold before the Auction.