Tut9 multicollinearity
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This document discusses testing for multicollinearity when estimating a multiple regression model. It provides an example using CEO salaries as the dependent variable and firms' sales, market value, and profits as independent variables. It notes that high multicollinearity between independent variables can make it difficult to judge their individual significance. The document recommends dropping variables, transforming data, changing the model specification, or obtaining a new sample as potential remedies when multicollinearity is detected.
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Call us at : 08263069601
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Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
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Call us at : 08263069601
(Prefer mailing. Call in emergency )
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