What assumption is made about the residuals in linear regression?

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Question: What assumption is made about the residuals in linear regression?

Options:

Correct Answer: They should be normally distributed

Solution:

One of the key assumptions of linear regression is that the residuals (errors) should be normally distributed.

What assumption is made about the residuals in linear regression?

What assumption is made about the residuals in linear regression?

Step 1: Understand what residuals are. Residuals are the differences between the actual values and the predicted values from the linear regression model.
Step 2: Know that in linear regression, we make certain assumptions about these residuals.
Step 3: One important assumption is that the residuals should be normally distributed, which means they should follow a bell-shaped curve when plotted.
Step 4: This normal distribution of residuals helps ensure that the predictions made by the model are reliable and valid.

Normality of Residuals – In linear regression, it is assumed that the residuals (the differences between observed and predicted values) are normally distributed, which is important for hypothesis testing and confidence intervals.