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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.
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.
SS Total
SS Total is the amount of error revealed by the empty model (the mean); it is the total area of the squared residuals based on the distance of each score from the mean.
xpnorm()
The xpnorm() function will generate the probability and z-score for a value (X) based on the mathematical function for a normal distribution. It can do this with just three pieces of information: the border you are interested in, and the mean and ...