Boston ejemplo (Gsheet)

Boston is best known for its famous baked beans, Fenway Park, The Boston Marathon, and of course, for the bar from Cheers. Many Americans consider them the best city in the USA. And of course, it can be a very expensive city to live in. All city zones have different house prices, and we want to discover why and what factors influence this.

This dataset contents the following columns:

• CRIM (per capita crime rate by town).
• ZN (proportion of residential land zoned for lots over 25,000 sq.ft.).
• INDUS (proportion of non-retail business acres per town).
• CHAS (Charles River dummy variable -= 1 if tract bounds river; 0 otherwise-).
• NOX (nitrogen oxides concentration -parts per 10 million-).
• RM (average number of rooms per dwelling).
• AGE (proportion of owner-occupied units built prior to 1940).
• DIS (weighted mean of distances to five Boston employment centers).
• RAD (index of accessibility to radial highways).
• TAX (full-value property-tax rate per \$10,000).
• PTRATIO (pupil-teacher ratio by town).
• B (from formula 1000(Bk – 0.63) 2 where Bk is the proportion of African American people in town).
• LSTAT (lower status of the population -percent-).
• Target: is the median owner-occupied home value in dollars divided by 1000. As our target variable is a continuous variable, we have a multi-variate regression problem.