The regression analysis below rotates the value of new car sales (In millions of dollars) and the independent variables "compensation" (in billions of dollars) and "employment level In the non-agricultural sector" (In thousands) for 44 consecutive quarters. Compare this multiple regression to the simple regressions with compensation and employment level of the respective Independent variables. Which of the following Is the likely culprit of the dramatic Increase In the p-value for employment level in the multiple regression? 1. Nonlinearity.
2. Heteroskedasticity.
3. Multicollinearity
4. None of the above.

The answer is option (3) Multicollinearity

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Step-by-step explanation:

Solution

The method that would be responsible for causing the p-value to increase or go higher is Multicollinearity.

Multicollinearity: Refers to a method where variables that are independent in a regression model are associated.

This correlation or association of variables tends to be a problem, because variables that are independent should remain independent.

y=1/4x-4

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image result for what is another name for consecutive interior angles? ​

when two lines are crossed by another line (called the transversal): the pairs of angles on one side of the transversal but inside the two lines are called consecutive interior angles. in this example, these are consecutive interior angles: d and f.

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