Question

How to calculate the residual standard deviation of the outcome from a model using residual SS, df, and AIC?

Answer 1

To calculate the residual standard deviation of the outcome from a model, divide the residual sum of squares (RSS) by the degrees of freedom (df) to get the mean squared error (MSE), and then take the square root of the MSE to get the residual standard deviation.

Step-by-step explanation:

To calculate the residual standard deviation of the outcome from a model, you can use the residual sum of squares (RSS), degrees of freedom (df), and Akaike information criterion (AIC). Here's how you can calculate it:

1. Calculate the mean squared error (MSE) by dividing RSS by the degrees of freedom.
2. Take the square root of the MSE to get the residual standard deviation.

For example, if the RSS is 100, the df is 50, and the AIC is 500, you can calculate the residual standard deviation as follows:

• MSE = RSS / df = 100 / 50 = 2
• Residual standard deviation = √MSE = √2 ≈ 1.41