ISSS608 2016-17 T1 Assign1 CHIA Yong Jian

Problem and Motivation

The public housing resale market is a closely watched market. A quick search on news revealed that the public housing resale market movement is watched closely almost on a monthly basis, especially for indicators hinting the stability or trend of the prices. These are crucial information not just for real estate companies, but also buyers and sellers of resale flats. This analysis is focused on providing relevant information that can aid buyers and sellers of resale flats to make informed decisions when deciding to buy or sell a flat.

• For buyers, they include newly-wed couples that may urgently need a house for their family needs. Knowing the prices of resale flats by areas can allow them to decide on a suitable area for house-hunting depending on their budget and preferences for amenities in the area
• For sellers, they are existing house owners that might be watching the market to understand the general market trends to decide on a good price to sell their houses.

We assume that the buyers are sellers are the general population where they might be untrained in statistics. Hence, charts would be generally designed from an approach that are visually attractive without unnecessary fluff, and requires little time for them to understand without requiring statistical knowledge.

Approaches

Data Acquisition

From Data.gov.sg

The dataset used to answer the above questions can be found from https://data.gov.sg/dataset/resale-flat-prices . There are two datasets available on the webpage. We will be using the resale flat prices data that includes data for the year 2015 to first half 2016, to answer the questions required.

From HDB Website

Supplementary data from HDB website is used to understand better the resale flat supply by the 23 towns and 3 estates planned by HDB, by normalizing the resale flats sold by the total flat supply in the area. The data is retrieved from http://www.hdb.gov.sg/cs/infoweb/about-us/history/hdb-towns-your-home .

Dataset Variables

In the data.gov.sg dataset, a quick review of the variables reveals no missing data.

The dataset includes the following variables:

Variable Name	Description	Example Levels/Values
Month	The 4-digit year and 2-digit month of the transaction	From “2012-03” to “2016-06”
Town	Includes the 23 towns and 3 estates under HDB planning	ANG MO KIO BEDOK BISHAN
Flat Type	The flat type sold. More information can be gotten from HDB: Types of Flats	1 ROOM 5 ROOM EXECUTIVE
Block	The block number of where the flat was sold.	99C 99B 977
Street Name	The street name in the town or estate where the flat was sold.	ZION RD YUNG SHENG RD WHAMPOA WEST
Storey Range	The storey of the flat sold. Ranges from first floor to highest fifty-first floor. Floors are binned to groups of 3 to 5, and may include overlaps	01 TO 03 25 TO 27 43 TO 45
Floor Area Sqm	The floor area of the flat sold. Ranges from 31 to 280 square metres.	45 74 92
Flat Model	The model type of the flat sold. There are 19 types. Details of the different flat models can be view on a website providing comprehensive information: HDB History and Floor Plan Evolution	Adjoined Flat Model A New Generation
Lease Commencement	The starting year of the flat lease, typically a 99-year period	1966 2004 2013
Resale Price	The transacted price of the flat sold.	$195,000 $515,000 $1,088,888

Data Modelling

The following are changes made before charting was done on Tableau:

Variable	Changes Made	Rationale
Example	Example	Example
Example	Example	Example