Develop an approximate prediction interval

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Reference no: EM132753921

Banks that make good decisions on loan applications are more profitable. Credit scoring is the statistical technique that helps banks make those decisions. However, many branches overturn credit scoring recommendations, while other banks do not use the technique. In an attempt to determine which factors affect loan decisions, a statistician surveyed 100 banks and recorded the percentage of bad loans (any loan that is not completely repaid), the average size of a loan, whether a scorecard is used, and if so, whether the scorecard recommendations are overturned more than 10% of the time. The data can be found in the Practice Final Exam Workbook.

Problem a. Perform a regression analysis, state the regression equation and assess the fit. Use as a baseline the case where scorecard recommendations are overturned less than 10% of the time

Problem b. Interpret the slope coefficients and the t tests of those slope coefficients. What do they tell you?

Problem c. Develop an approximate 95% prediction interval of the percentage of bad loans for a bank whose average loan is $10,000 and which does not use a scorecard

Reference no: EM132753921

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