Page available at: https://faisaljina.github.io/data-analytics-dashboard/

Stat testing, visualisation and dashboarding

The House Price Index (HPI) from gov.uk is a dataset used by many companies to track changes in the domestic housing market. This project uses R to examine the short- and long-term trends in this data, including the building of an RShiny dashboard.

Features

• EDA
• Visualisation
• Hypothesis Testing
• Dashboarding

Techniques

• Linear Regression Modelling
• Shapiro-Wilk Normality Testing
• Welch 2-Sample T-Testing
• RShiny

Summary

1. The House Price Index (HPI) dataset from gov.uk was examined.
2. The trends in the regions of Great Britain were compared using a line graph.
3. The 10-year trend in Britain was modelled and statistically analysed, and a dashboarded graph created.
4. Boxplots were used to examine regional variation over this time - this was also dashboarded to allow realtime boxplot generation from selecting graph areas.
5. Short-term trend differences between the groups were tested first for normality, then t-tested for difference between the groups.
6. The outcome showed significant difference between the Wales and England trends, so this was visualised, dashboarded and discussed.

The RShiny Dashboard is available at: https://faisaljina.shinyapps.io/dataanalyticsdashboard/