Hi Siva, I think David Wang has provided a method that posted couple months ago. I copy the message for you, as shown below:  BTW, there is a caveat that the approximation of 95% confidence interval by "two sigma" can only be used when the degree of freedom is sufficient large. This student's ttable makes it clear (t = slope/sigmab). http://www.ncsu.edu/chemistry/resource/ttable.html D. On Thu, Mar 5, 2009 at 7:08 PM, David Wang <climater@xxxxxxxxx> wrote: Hi Ferreters, I recently wanted to calculate the 95% confidence interval for a linear regression by the way of regresst.jnl, and found it's quite straightforward. There is a question on this in the archive that remains unanswered (http://www.pmel.noaa.gov/maillists/tmap/ferret_users/fu_2006/msg00428.html). So I put forth my two cents here risking everybody has already known it. The idea is that 95% confidence interval is about "two sigma" (http://en.wikipedia.org/wiki/Uncertainty#Measurements). So the problem boils down to estimating the sampling standard deviation of the regression slope. Following Wilks's book (statistical methods in atmospheric science, chapter 6.2), the sampling distribution for slope is Gaussian and its sampling standard deviation is given in the equation 6.18b. In Ferret, after regresst.jnl, issue the following two commands: let >let sigmab = ((qvar/pvarslope*slope)/(ones[t=@sum]2))^0.5 And the 95% error bar is 2*sigmab. If the confidence interval at a different significance level (say, 90%) is desirable, one can simply go to the lookup table for the ttest and figure out how many "sigma" s/he needs. HTH, D.   On Fri, 8/7/09, siva <sivamtech07@xxxxxxxxxxxxxx> wrote:
