You work for the Ministry of Housing. We are facing a potential housing crisis as we...

  

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You work for the Ministry of Housing. We are facing a potential housing crisis as we believe we are in a Real Estate bubble. We need to identify a few things for our leadership to help them make informed decisions: 1. What is the rate of increase for homes in Boston in the last year, 2 years and 5 years? 2. Identify the main variables that are impacting the price of a home. 3. Use macro-economic trends and housing market information to predict the average home prices in 3 months, 6 months, 1 year and 3 years. 4. Identify the distribution of homes in Boston and their affordability by classifying them into one of three buckets - cheap, normal and expensive. This would mean we'd have to make a prediction about the house's classification even though it's not listed on the market. We'd have many data points to help make the prediction like the average sale price in the area, # of bedrooms, square footage, etc. 3. For each of the four questions above, identify which ones you'd apply clustering analysis to help answer the question and why? Recall clustering analysis can be used to segment data into natural clusters whereby the most similar entities exist in a given cluster. (4 marks) You work for the Ministry of Housing. We are facing a potential housing crisis as we believe we are in a Real Estate bubble. We need to identify a few things for our leadership to help them make informed decisions: 1. What is the rate of increase for homes in Boston in the last year, 2 years and 5 years? 2. Identify the main variables that are impacting the price of a home. 3. Use macro-economic trends and housing market information to predict the average home prices in 3 months, 6 months, 1 year and 3 years. 4. Identify the distribution of homes in Boston and their affordability by classifying them into one of three buckets - cheap, normal and expensive. This would mean we'd have to make a prediction about the house's classification even though it's not listed on the market. We'd have many data points to help make the prediction like the average sale price in the area, # of bedrooms, square footage, etc. 3. For each of the four questions above, identify which ones you'd apply clustering analysis to help answer the question and why? Recall clustering analysis can be used to segment data into natural clusters whereby the most similar entities exist in a given cluster. (4 marks)