MSA 2020 phase1 Data Science (Housing Analysis Project)

Task

• Using the provided house price dataset as a base, add at least 2 extra columns/features. This can be the 2018 Census Population and the Deprivation index or another feature. Refer to the Data Collection section for instructions on how to do this.

• Using either R or Python, analyse the resulting dataset. This would include preprocessing the data, exploring patterns in the data and building a machine learning model. You may get some inspiration from the 'Data Analysis and Model Building' section.

• As the final output of the assignment, produce a report of detailing your findings from above. This should include an:

  • Executive Summary
  • Initial data analysis
  • Analysis of correlations and patterns in the data
  • Build a model and comment on it (eg. if you did not include any attributes, why did you drop them)
  • Conclusions

• The 'report' can be a pdf written in Microsoft Word or Azure/Jupyter notebook with markdown or a R markdown file. Submit your dataset, Rmd/notebook files and report (in pdf format).