2. You want to determine whether the length of time a customer has been buying your products from your company is an important variable that affects/drives their likelihood to respond to a marketing coupon. But all you have is the date when they first purchased a product from you. What could you do to generate duration of customer (e.g. how long the person has been your customer). Answer in one to two sentences.

2. One of your driver variables in a data set is Town Population. The majority of the records in the town population variable range from a low of towns with 5,000 people to towns with as many as 30,000. However, one of the towns in your data has a population of 850,000.

What is this data point 850,000 referred to? (technical name)

Would you include it in your data when you conduct your mining analysis? (yes/no answer)

4) You have mined your data with a neural network and your R^2 came up with (.99). Describe two important potential reasons why your model produced near perfect results? Answer in a few sentences

5) The data miner wants to generate a decision tree that illustrates the patterns that exist between driver variables and the target variable because the business team can better relate to this type of modeling. Which method would they use. Place an x before one of the methods below.

__ regression __ Clustering __segmentation __ Neural Nets

6) The data miner wants to identify how price and advertising drive sales for the company and wants to forecast but does not like to use algorithms. Place an x before one of the methods below.

__ regression __ Clustering __segmentation __ Neural Nets