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A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies. She proceeds to randomly select 26 large corporations and record information in millions of dollars. A statistical analyst discovers that capital spending by corporations has a significant inverse relationship with wage spending. What should the microeconomist who developed this multiple regression model be particularly concerned with? a. Missing observations b. Collinearity c. Normality of residuals d. Randomness of error term

User Alvis
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Answer: option b

Step-by-step explanation: In simple words, collinearity refers to the condition under which some of the Independent variables in the model are related to each other. This international between independents variables can result into incorrect results while fitting the model.

Therefore, collinearity causes problem as the analyst prepares a model on the basis that there will be two inputs one is dependent another is independent but due to this phenomenon the expected input structure collides.

Hence from the above we can conclude that the economist should be concerned with col linearity.

User Thiago Silva
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