# 95% CI that contradict a paired samples t-test

I conducted a paired samples t-test to analyse the effect of an exercise intervention on blood pressure measurements. The test demonstrated a significant p-value. However, when I have calculated 95% confidence intervals for the mean difference between pre and post measures the result suggested there to be no significant difference between pre and post measures, i.e lower level minus and upper level positive. Is this possible?

• How did you calculate the 95% confidence interval and what is the sample size?
– user10525
Commented Aug 14, 2012 at 13:07
• The sample size is 10 and I calculated the Confidence interval by finding the mean difference between pre and post mean values, then found the square root of the STD of group one squared/ 10 plus the square root of the STD of group two squared/10. Then I multiplied this figure by 1.96. and added or substracted this value from the mean diff to get upper and lower level confidence intervals . Commented Aug 14, 2012 at 13:23
• Your intuition is right--this shouldn't happen. However it can happen if two different procedures are used. Eg, 1 thing I've seen several times is someone runs a paired t-test & then presents the results w/ a bar chart w/ 1 bar for pre & 1 for post, & the CI's overlap, causing confusion & anxiety. The analogous plot would have just one bar for differences w/ a CI that doesn't include 0. We need to know a lot more about your data & how you got these discrepant values, as @Procrastinator suggests. Commented Aug 14, 2012 at 13:23
• @GinaRutherford Have a look at this tutorial in R. Also, note that t.test(data1,data2,paired=TRUE) in R gives you a confidence interval based on this test.
– user10525
Commented Aug 14, 2012 at 13:40
• The procedure you used to calculate the CI is incorrect. Use the procedure outlined by @drknexus below in the second paragraph. Commented Aug 14, 2012 at 13:43