CI for Dependent Variable in Multiple Linear Regression

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Carl
Carl 2016-2-25
I have a regression model but I want to get a 95% confidence interval of the dependent variable for given values of the independent variables.
On the net I found that for a single factor regression: Confindance interval = t(alpha, DofF) * SYX * SQRT(1/n+(X-XAVG)^2/SSX)
where n is the number of observations, XAVG is the average of all the independent variables and X is the value for X for which the CI is wanted.
Is there a way to extend this to multiple linear regression (I have 3 factors)? Can I get the sum of squares values in the basic module of Matlab other than from first principles ?
Thanks

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