MOVING TO MANCHESTER?

THE PROJECT AIM

This project involved identifying the information a prospect client would consider, i.e., Transport, General Practices in the area, and School Performances across each area.

The potential client target would be someone with children or dependencies, and a budget of £300,000 for a house, therefore data was gathered from open-source environments such as GOV.UK for data on schools and OFSTED ratings.

THE LINEAR REGRESSION MODEL

A linear regression model is applied to the data provided to predict house prices over the next year to support the client’s decision -making.

A key factor incorporated into the linear regression model was the rate of house price increases in each area. This provided insights into whether house price trends in specific locations were consistent or erratic, enabling the client to evaluate long-term market stability. Another crucial consideration during dashboard development was the popularity of Manchester's property market. Recognising the potential for resale in the future, I included metrics to help the client make informed, proactive decisions about purchasing a property with strong resale value. After all, no one wants to invest in a home that might depreciate in value over the next 5 to 10 years.

THE METHODOLOGY

For the "Moving to Manchester" project, data was gathered on transport links and general practice locations to help the potential client assess accessibility to essential services, such as healthcare and transport, for themselves and their child.

Additionally, mock future dates were generated in Power BI to support linear regression modelling, allowing the client to analyse predicted average house prices over the coming months.