> library(boot)

> data(aircondit)

> aircondit$hours
 [1]   3   5   7  18  43  85  91  98 100 130 230 487

> t.test(aircondit$hours)

	One Sample t-test

data:  aircondit$hours 
t = 2.7483, df = 11, p-value = 0.01895
alternative hypothesis: true mean is not equal to 0 
95 percent confidence interval:
  21.52561 194.64105 
sample estimates:
mean of x 
 108.0833 


> samplemean = function(x, i) {
    mean(x[i])
}

> b = boot(aircondit$hours, samplemean, 1000)

> boot.ci(b)
BOOTSTRAP CONFIDENCE INTERVAL CALCULATIONS
Based on 1000 bootstrap replicates

CALL : 
boot.ci(boot.out = b)

Intervals : 
Level      Normal              Basic         
95%   ( 33.2, 181.6 )   ( 18.9, 166.3 )  

Level     Percentile            BCa          
95%   ( 49.8, 197.3 )   ( 59.9, 236.6 )  
Calculations and Intervals on Original Scale
Some BCa intervals may be unstable