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Quantium Quants


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Evidence of Work

Quantium Challenge: Second-Hand Goods Roundabout

Project Info

Quantium Quants thumbnail

Team Name


Quantium Quants


Team Members


5 members with unpublished profiles.

Project Description


We developed a web application for Roundabout employees to use and determine which suburb in the ACT is most likely to donate second-hand baby goods. We utilised the ABC socio-economic index data set and the ACT education database to include several factors such as the number of primary schools in a region, the number of families in a particular suburb and the number of children those families have into our propensity score in order to integrate this into the web application we develop.

The solution will enable Roundabout employees to figure out propensity scores in different ACT suburbs so that they will be able to determine which suburbs will be best to collect from.


Data Story


Our main source of data is taken from the ABS Socio-Economic Indexes for Areas, in which we take a look at the relative index of relative socio-economic advantage and disadvantage of people living in ACT. We also utilised data from the ACT education directorate.

What we aimed for is to come up with a propensity score that is going to determine which suburb in ACT will be the most likely to donate their second-hand goods. We included many different factors and components such as the number of schools located in a particular suburb, the number of families, the number of children those families have as well as their age differences - these are a few examples of data that we integrated into our propensity score formula in order to help develop our web application solution.


Evidence of Work

Video

Homepage

Team DataSets

Socio-Economic Indexes for Areas

Description of Use We use this data to develop a propensity score that is going to help us determine which suburb has the most likelihood to donate baby and children's second-hand goods.

Data Set

Koori Preschools

Description of Use We use this data to develop a propensity score that is going to help us determine which suburb has the most likelihood to donate baby and children's second-hand goods.

Data Set

Census of ACT Schools (February 2022)

Description of Use We use this data to develop a propensity score that is going to help us determine which suburb has the most likelihood to donate baby and children's second-hand goods.

Data Set

Schools ABS

Description of Use We use this data to develop a propensity score that is going to help us determine which suburb has the most likelihood to donate baby and children's second-hand goods.

Data Set

List of Non-Government Schools

Description of Use We use this data to develop a propensity score that is going to help us determine which suburb has the most likelihood to donate baby and children's second-hand goods.

Data Set

Public Primary Schools

Description of Use We use this data to develop a propensity score that is going to help us determine which suburb has the most likelihood to donate baby and children's second-hand goods.

Data Set

Preschools (Public)

Description of Use We use this data to develop a propensity score that is going to help us determine which suburb has the most likelihood to donate baby and children's second-hand goods.

Data Set

ACT Population Projections by Suburb (2015 - 2020)

Description of Use We use this data to develop a propensity score that is going to help us determine which suburb has the most likelihood to donate baby and children's second-hand goods.

Data Set

Challenge Entries

Finding potential donors to support families in need

How can we identify where families who might have second-hand baby and children's goods to donate live, and estimate the volume of goods that could be donated to families in need through organisations such as Roundabout?

Eligibility: Eligible submissions will support organisations such as Roundabout to identify where families with items to donate might be, how many items they may have, and/or the impact of cost of living on service demand and/or donations.

Go to Challenge | 10 teams have entered this challenge.