Milestone Report Capstone Project of the Coursera Data Science Specialization

The Boston Housing Data Set was gathered by Harrison, D. and Rubinfeld, D.L. for their study 'Hedonic prices and the demand for clean air' (Journal for Environmental Economics & Management, vol.5, p 81-102) in 1978. In the data set several variables were measured that influence house prices in Boston (and throughout the whole world). The user of the App can set the values of the variables through the slider bars to the left side of the screen. The user can push the 'Submit Now' button to calculate the prediction according to the models. The slider bar default values are the means of the Boston Housing Data Set. The first screen that the user sees is the prediction based on the default values of the data. Because the models first have to be calculated, the user must allow a few tens of seconds for the first plot and values on the screen to be seen.

Submission of the 3rd week assignment for the Coursera course Developing Data Products

This publication provides an interactive map generated through Leaflet in R. Many thanks to Arthur Charpentier, who combined data from the French INSEE (Institut National de la Statistique et des Etudes Economiques) to a data set which lists the population per Region, Départment or Commune. I took the lowest level (Commune), which provides a list of over 36.000 areas with the registered population. Fans of holiday in France can use this to determine the area they want to go, either busy or quiet.

The objective of the research was to identify the weather event types across the United States that: 1. are most harmful with respect to population health 2. have the greatest economic consequences based on the NOAA Storm Database