The random error in a regression equation
A) is the predicted error.
B) includes both positive and negative terms.
C) will sum to a large positive number.
D) is used the estimate the accuracy of the slope.
E) is maximized in a least squares regression model.

Question

Quizplus · Accepted Answer

The random error in a regression equation refers to the variation in the response variable that cannot be explained by the predictor variable(s). It includes both positive and negative terms, as it represents the deviation of the observed values from the predicted values. It is not necessarily a large positive number, as it can be small or large, and positive or negative. It is also not used to estimate the accuracy of the slope, as that is determined by the standard error of the slope. It is not maximized in a least squares regression model, as the objective of the model is to minimize the sum of squared errors.

The Random Error in a Regression Equation