Analyzing Business Statistics and Housing Market Data

Running head: BUSINESS STATISTICS
Business Statistics
Name of the University
Name of Student

BUSINESS STATISTICS1
Table of Contents
Introduction:...............................................................................................................................3
Sorting the data:.........................................................................................................................3
Analysis:.....................................................................................................................................3
References:.................................................................................................................................8

BUSINESS STATISTICS2
Introduction:
A set of data is given to us with information about the house prices and related
information. It is needed to analyse the properties of the related variables and present the data
in a form that reveals information about the housing market. The variables given for analysis
are suburb, the address of the street, the number of bedrooms in the house, the price, the
status of sale of property, the type of property and the agent through whom the property is
bought.
The meaning of the result property is mentioned in the sheet as:
S- Property Sold, SP- Property Sold Prior, PI: Property Passed in: PN: sold prior not
disclosed, SN- Sold Not Disclosed, NB- No bid, VB- Vendor Bid, W- Withdrawn Prior to
Auction, SA- Sold After Auction, , SS-Sold after auction price not disclosed, N/A- price or
highest bid not available.
Sorting the data:
Any data collection method may contain errors as data collection in the real world is
complicated .Before analysis is done the data needs to be sorted for any discrepancies in the
data type. It is observed that there are blanks in Bedroom and N/A in the price section that
will create complication in computation of statistics of the data.
Sorting the data is done in a few steps. First the data is sorted by bedrooms. Unusual entries
consist of 1 bedroom, 10 bedrooms or 15 bedrooms. Also few property’s bedrooms are left
blank. Then the price is checked for any unusual entries. It is seen that some property prices
are listed as N/A.
The data set is filtered appropriately for calculating different statistics. And the clean data is
presented in the same excel worksheet. The sorted data does not contain the values of the data
set for which the number of bedrooms are left as blank and the Price value is listed as N/A.
Analysis:
With the new sample various statistics are calculated and the results are presented
below.
The price range of the house is divided into class width of size 100,000 from $348,000 to
$634,799. It can be seen that the number of houses with price more than 264,799 are
relatively few and the highest number of houses lie between the ranges $134, 8000 and
$144,7999 with a total of 9.6% of the total houses( Siegel, 2016).