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In linear regression, what does the term 'residual' refer to?

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Question: In linear regression, what does the term \'residual\' refer to?

Options:

  1. The predicted value of the dependent variable
  2. The difference between the observed and predicted values
  3. The slope of the regression line
  4. The intercept of the regression line

Correct Answer: The difference between the observed and predicted values

Solution: 

A residual is the difference between the observed value and the predicted value in a regression model.

In linear regression, what does the term 'residual' refer to?

Practice Questions

Q1
In linear regression, what does the term 'residual' refer to?
  1. The predicted value of the dependent variable
  2. The difference between the observed and predicted values
  3. The slope of the regression line
  4. The intercept of the regression line

Questions & Step-by-Step Solutions

In linear regression, what does the term 'residual' refer to?
  • Step 1: Understand that in linear regression, we create a model to predict values based on input data.
  • Step 2: When we use this model, we get predicted values for our data points.
  • Step 3: The observed value is the actual value we have from our data.
  • Step 4: A residual is calculated by subtracting the predicted value from the observed value.
  • Step 5: The formula for a residual is: Residual = Observed Value - Predicted Value.
  • Residuals in Linear Regression – A residual is the difference between the observed value and the predicted value in a regression model.
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