Which of the following is NOT a principle assumption about linear regression?

The chosen answer highlights an important aspect of linear regression assumptions. While the presence of autocorrelation in the residuals of a regression model indicates a violation of one of the core assumptions, it is important to clarify that the term "no autocorrelation" is not explicitly listed as a primary assumption of linear regression.

Linear regression fundamentally assumes that the dependent and independent variables exhibit a linear relationship, the errors of the model are not serially correlated, and they follow a normal distribution with constant variance. Each of these principles aids in ensuring the reliability and validity of the model's estimates.

The presence or absence of autocorrelation is related to the assumption about the errors but is not defined as an assumption in the same manner as the linear relationship or normal distribution. This nuance is critical in understanding linear regression, as it emphasizes how underlying statistical theories can inform model assessment and diagnostics without being explicitly stated as assumptions.

Thus, the correct answer is based on the premise that the terminology and framing of "no autocorrelation" might imply a more specialized diagnostic consideration than what the foundational assumptions of linear regression entail.