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Consider the following case of decision-making on loan applications.  You are a bank executive with thousands of records on customers who were given loans.  Each record has many fields, such as amount of loan, credit score, annual income, employed or not, years with current employer, years at current residence address, marital status, zip code of residence, numerical rating of strength of personal references, etc., including a field called "outcome" that has a categorical data value (either "paid back" or "defaulted") based on the outcome of giving that person a loan. 

You want to analyze data to learn more about your business and customers. Toward this goal, provide one (and only one) specific example question that you might want to address using each of the data analysis techniques below and provide an example of a result you might get you're your analysis. For each question, your answer should be in less than 50 words, including 1 sentence stating the example question and 1 sentence describing a potential result.

a) Classification

b) Regression

c) SQL Querying

d) Clustering

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