Methods
The Software used to perform the exploratory data analysis is GeoDa \cite{geoda}, a free open source software that provides tools for geospatial analysis. We will first make a basic statistical analysis of the data distribution using a scatter plot of the thermal radiation versus the noise experienced during the day. However, this method only lists the point and does not give an idea of the spatial distribution of the data.
For this reason we will add a co-location map of the two variables. To create a co-location map, we first need to divide each set of data into quantiles. We decided to use four quantiles, as a bigger number would lead to spreading the data too much to be relevant, while a lower number has the risk of grouping together points that could be very different, depending on the repartition inside the dataset. This co-location map will then show which points of each variable appear in the same quantile. This is a very useful tool to assess the correlation between two variables while also showing their location, allowing the reader to pick out different regions of the town. This will be useful because the population and activity are not spread out evenly across Geneva. The analysis will focus on finding hot spots in the city where the correlation might be significantly high or low.
Results