Can it be possible that confidence intervals of two estimates intersect but the difference between estimates is statistically significant?

I can see the opposite result when CIs of two estimates do not intersect, yet the difference is not statistically significant. Consider CI(b2) includes 0 but does not include b1. As the difference usually has wider CI than b2, CI(b1 - b2) therefore includes 0.

Can anybody give an example when the difference is statistically significant indeed? Simulated calculations would be a nice illustration to the proof.


1 Answer 1


This was straightforward to produce an example of.

Here's a plot of two data sets with 95% CI for the population mean for each, showing substantial overlap:

Stripchart of samples, overlap in CIs is about 40% of the width of each interval

But the ordinary two sample t-test of the difference in means is significant at the 5% level (p=0.0487).

The samples:

x <- c(-0.298962792076644, 1.31710182405988, -0.0766589533299794, 
0.0337168103544878, 0.613459873853599, -0.15890274057914, -0.390659755933809, 
1.53050298362584, 0.0499823542564353, 0.466616365382981, 0.744105279446008, 
0.347365715075919, -0.390328944660933, -1.51499397031234, 0.307921692331803)

y <- c(2.24809443786109, 1.19177585960823, 0.199827407525814, 0.250899031428787, 
1.23762215395455, -0.154050289186218, 0.457502634532336, -0.783354267205565, 
1.3261971790762, 1.00561325604448, 1.40114939526361, 2.15511419519248, 
-0.211169335193589, 1.17701452262601, 0.220094909794722)

The two-sample test:


        Two Sample t-test

data:  x and y
t = -2.0606, df = 28, p-value = 0.04874
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -1.215344491 -0.003597556
sample estimates:
mean of x mean of y 
0.1720177 0.7814887

The CI's for each sample mean (some lines omitted):


95 percent confidence interval:
 -0.2392346  0.5832701
mean of x 


95 percent confidence interval:
 0.298467 1.264510
mean of x 

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