You can get this number yourself using the qnorm function.
The qnorm function is a little like the opposite of the pnorm function that we saw in the previous chapter. That function started with a p because it gave us a probability—the probability that we would see a value equal to or below it in a normal distribution. The q in qnorm stands for quantile. A quantile, for a given probability, is the value at which the probability will be equal to or below that probability.
I know that was confusing! stated differently, but equivalently, a quantile for a given probability is the value such that if we put it in the pnorm function, we get back that same probability:
> qnorm(.025)  -1.959964 > pnorm(-1.959964)  0.025 ...