As a Data Scientist with a housing agency in Boston, MA, this project aims to provide valuable insights into housing prices based on a dataset derived from the U.S. Census Service. The analysis is conducted to aid upper management in making informed decisions. Four key questions are addressed to uncover meaningful patterns and relationships within the data.
Is there a significant difference in the median value of houses bounded by the Charles river or not?
Is there a difference in median values of houses based on the proportion of owner-occupied units built before 1940?
Can we conclude that there is no relationship between Nitric oxide concentrations and the proportion of non-retail business acres per town?
What is the impact of an additional weighted distance to the five Boston employment centres on the median value of owner-occupied homes?
The analysis employs statistical techniques to address each question, offering insights and conclusions. Hypothesis testing, correlation analysis, and regression modeling may be utilized as appropriate.