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# How did we get 1.96?

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] -1.959964
> pnorm(-1.959964)
[1] 0.025 ...```

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