The coursework is based on undertaking an analysis of a real world data set. It is a shared assessment block for Quantitative Data Analysis and Modern Data taught in the Brunel University London.
For this Coursework we are working with house-analysis.RDa which has 90377 observation with 12 Variables.
Information regarding the Variables are below,
| Variable (Column Name) | Description |
|---|---|
| id | Property id |
| Price | Sale price of the property |
| mq | Total square meters of the property |
| Floor | Entrance floor of the property |
| n_rooms | Total number of rooms |
| n_bathrooms | Total number of bathrooms |
| has_terrace | Property has a terrace |
| has_alarm | Property has an alarm |
| heating | Type of heating (“autonomous”, “ other”) |
| has_air_conditioning | Property has Air conditioning |
| has_parking | Property has parking |
| Is_furnished | Was the property sold with its contents (furnishings) or not? (0,1) |
Our Objective for this Coursework is as follows,
- Create a subset of data from the house-analysis.RDa
- Organise and clean Data
- subset the data into the specific data subset allocated
- data quality analysis
- data cleaning
- Exploratory data analysis
- Modelling
- explain your analysis plan
- build a model for property price
- critique your model using relevant diagnostics
- based on the previous sections suggest improvements to your model
- Extension work
- Model the likelihood of a property being furnished (using the is_furnished variable provided)
- We used Linear Regression model for the property price and critiqued the model using relevant diagnostics
- For the likelihood of property being furnished , we build a model based on the Logistic Regression