Mean Square (MS)

Mean Square (MS)

Mean Square (MS) is also called variance; approximated by the sum of squares (SS) divided by the degress of freedom (i.e., n-1); the MSE from the empty model can be thought of as roughly the average squared deviation.

    • Related Articles

    • mean()

      The mean() function computes the mean of a variable. Example: # Calculate the mean of Thumb mean(Fingers$Thumb) # Alt: use 'data =' argument instead of '$' (produces same output) mean(~Thumb, data = Fingers) Example output:

    • mean

      Mean is the average, the number in the distribution that balances the residuals.

    • grand mean

      Grand mean is the mean for everyone in the sample.

    • variance

      Variance is also called MS, Mean Square; approximated by the sum of squares (SS) divided by the degrees of freedom (i.e., n-1); the MSE from the empty model can be thought of as roughly the average squared deviation.

    • sqrt()

      The sqrt() function computes the square root of a value. Example 1: # Calculate the square root of 157 sqrt(157) Example output: Example 2: # Use sqrt() to get the standard deviation around the mean of Thumb empty_model <- lm(Thumb ~ NULL, data = ...