I'm reading this pdf on statistics. I wanted to ask the difference between sections 3.5 and 4.2.
In section 3.5 it is described how to compute, from a sample, an estimate of the mean with a confidence interval, using the sample mean and sample variance. This was computed using the standard way of doing it.
In section 4.2 it makes a null hypothesis for the value of the mean, and develops a hypothesis test for rejecting or accepting the hypothesis. The hypothesis test was based simply on the fact that the standardized variable, under the assumption of having mean $m$ as the null hypothesis, should be nearly Gaussian for large $n$ (or having a $t$ distribution for small samples).
I did not understand actually the operational difference between the two approaches, which they seem to be quite similar to me, and the conceptual difference, if there is one.