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In linear regression, what does multicollinearity refer to?

Practice Questions

Q1
In linear regression, what does multicollinearity refer to?
  1. High correlation between the dependent variable and independent variables
  2. High correlation among independent variables
  3. Low variance in the dependent variable
  4. Independence of residuals

Questions & Step-by-Step Solutions

In linear regression, what does multicollinearity refer to?
  • Step 1: Understand that in linear regression, we use independent variables to predict a dependent variable.
  • Step 2: Recognize that independent variables are the factors we think influence the outcome.
  • Step 3: Know that multicollinearity happens when two or more independent variables are very similar or related to each other.
  • Step 4: Realize that this high correlation can cause problems in understanding which variable is actually affecting the dependent variable.
  • Step 5: Remember that multicollinearity can make it hard to trust the results of the regression analysis.
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