In simple linear regression, the denominator of the standard error of estimate s_{$\varepsilon$} is .

Question

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The denominator of the standard error of estimate for simple linear regression is the square root of the residual mean square, which is equal to the sum of squared residuals divided by the degrees of freedom (n-2). This expression is equivalent to the square root of the mean of the squared deviations of the predicted values from the observed values, which is also denoted as s or s.e.e. Therefore, the statement is true. However, the code (11eaa8e1_5374_e92c_93a6_f3a36a6bbbd3_TB4382_11) seems like a technical glitch or coding error and does not provide meaningful information related to the question.

In Simple Linear Regression, the Denominator of the Standard Error ε\varepsilonε

In Simple Linear Regression, the Denominator of the Standard Error $\varepsilon$