Assumptions of Simple Linear RegressionWhat will be the effect of the error terms not being homoscedastic in nature?You will not be able to fit a straight line through the data.The error terms will not be normally distributed. The inferences made on the model would be unreliable.Both B and C.
Question
Assumptions of Simple Linear RegressionWhat will be the effect of the error terms not being homoscedastic in nature?You will not be able to fit a straight line through the data.The error terms will not be normally distributed. The inferences made on the model would be unreliable.Both B and C.
Solution
The correct answer is "Both B and C". If the error terms are not homoscedastic, it means that the variability of the error terms is not constant across all levels of the independent variable. This violates one of the key assumptions of simple linear regression. As a result, the error terms will not be normally distributed and any inferences made on the model would be unreliable. This is because the standard errors of the coefficients will be biased, leading to incorrect confidence intervals and hypothesis tests.
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