Question: Why should you think carefully about any obvious outlier in
Why should you think carefully about any obvious outlier in the sample data set for a regression relationship, rather than simply removing it?
Answer to relevant QuestionsWhat determines the price of a used car? One of the factors is the odometer reading. A data set of the number of kilometres on the odometer and the asking price for a 2006 small sedan with an automatic transmission is ...Check the Excel output for the models created in Exercises 6, 7, and 8 above for outliers. If you had access to the original records for this data set, what would you do? Would it be appropriate to use the Woodbon model to make a prediction for mortgage rates of 6%, housing starts of 2,500, and advertising expenditure of $4,000? Explain why or why not. Create all other possible regression models for the Salaries data. The models will be based on the following explanatory variables: a. Years of postsecondary education alone b. Years of experience alone c. Age alone d. Age ...Create a multiple regression model for the Salaries data set that includes years of postsecondary education and years of experience as explanatory variables. Interpret the model.
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