How could you find a multi-dimensional outlier

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Reference no: EM133183865

You are interviewing for a job at a prestigious consulting firm that focuses on solving business problems using analytics. The following are the questions asked by the recruiting manager - they are based on real client problems and questions. For each question, provide a clear and concise answer that shows you understand the material from both a managerial and statistical perspective.

Your client is proposing a satisfaction survey which should generate about 5000 responses. One of the questions has potential responses 'very dissatisfied', 'dissatisfied', 'no opinion', 'satisfied' and 'very satisfied'. Since there is a natural ordering to these results, he is not sure if he should code the results 1,2,3,4,5 respectively or -2,-1,0,1,2 respectively. Explain and justify your thoughts on how the data should be coded, and any strengths and weaknesses the choice of coding has.

How could you find a multi-dimensional outlier in a linear regression context? What steps should be taken?

Your client is worried about the restrictions imposed on a linear model. She suspects some of the relationships have non-linear patterns like decreasing returns to scale or an exponential shape. What would you tell her?

Reference no: EM133183865

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