For truth in advertising, note that -1/sqrt(1+CVx^2) is the correlation, not
the covariance between slope and intercept estimates.

Jerry

"Jerry W. Lewis" wrote:

Standard errors of estimates (square root of variances) are given by LINEST
with the optional 4th argument set to TRUE. Covariances are not natively
available, but can be calculated from first principles.

For simple linear regression, the covariance between slope and intercept
estimates is
=-1/sqrt(1+CVx^2)
where CVx is =STDEVP(xdata)/AVERAGE(xdata)

For more general models that are linear in the unknowns, the covariance
matrix for estimates is
MINVERSE(MMULT(TRANSPOSE(xmatrix),xmatrix))*S^2
where S is the standard deviation given by LINEST with the optional 4th
argument set to TRUE. As a calculation, this can run into numerical problems
with complicated models. If you have Excel 2003, compare the variance of
estimates from this calculation with what LINEST returns; if they do not
agree, then this approach needs more numeric precision than is available in
Excel (Excel like most software uses IEEE double precision).

Jerry

"Moohwan" wrote:

I would like to report the estimated variances and covariances of the
estimated coefficients from regression using excel.
How could I do that?