Here is the scenario. Imagine I am a property developer in the Boston, MA area. I am looking for neighborhoods where there is opportunity for development or there is opportunities for home repair / reconstruction. I have been given a list of 506 neighborhoods. Each of the neighborhoods is described in my data set through 14 fields which are described in the data dictionary below.

Now Imagine that I am enlisting your assistance. Given that I have 14 figures for each neighborhood, I need you to mine through the data and see what you can tell me about it. Which neighborhoods are the best for me to consider seeking construction or remodel opportunities? Which ones are the more affluent? Which ones may have problems that I want to avoid? Which ones will be most appealing to home buyers? What else can you tell me about the data?

Here is the list of 14 fields that you have on each of the 506 neighborhoods in the data set:

• CRIM - Crime Rate
• ZN - Percentage of Residential land zoned for lots over 25,000 squared feet
• INDUS - Percentage of land occupied by non-retail business
• CHAS - Does tract bound Charles River? (=1 if tract bounds river, = 0 otherwise)
• NOX - Nitric oxide concentration (parts per 10 million)
• RM - Average number of rooms per dwelling
• AGE - Percentage of owner-occupied units built prior to 1940
• DIS - Weighted distances to five Boston employment centers
• RAD - Index of accessibility to radial highways
• TAX - Full-value property tax rate per $10,000
• PTRATIO -Pupil-to-teacher ratio by town
• LSTAT - Percentage of lower status of the population
• MED - Median value of owner-occupied homes in $10,000s
• CAT.MEDV - Is median value of owner-occupied homes in tract above $300,000 (CAT.MEDV = 1 or not (CAT.MEDV = 0)?

And here is the data set: