I agree that, for an intro class, working with the z-score + standard normal is probably unnecessary.
If your students go further, it's a useful example of the idea of a pivot, but you can probably explain that when they get there. On Thu, Apr 20, 2017 at 10:07 AM, David Monterde <dmonte...@me.com> wrote: > First of all I have to apologize because my english is horrible. > > I am working in a basic and practical statistic course. > > I will speak about confidence intervals, of course. > > But when I was preparing this chapter I had a doubt: I wonder if it has sence > today to explain the confidence intervals for a mean in terms of the standard > normal distribution. > > If we show that the mean follows a normal distribution with variance/n then > it is easy to explain (and to understand) that the confidence interval is due > to two percentiles, the percentile alpha/2 and the percentile 1-alpha/2 from > a normal distribution with the sample mean and the sample variance/n. > > I think that the standard gaussian distribution was usefull when we had to > calculate CI in the past. > That is, it was a simple way to have all possibilities in a single table (in > paper). > > But now, we have R functions that let us to obtain the exact values for any > normal distribution. > > I think that is not necessary to explain how to work with transformations if > we can explain that a CI is simply to identify percentiles. > > What do you think? > > Thanks > > PD I know that the normal distribution for CI need some hipothesis. But I > have focused the question > > _________________________ > > David Monterde > > Lo difĂcil se hace. > Lo imposible se intenta. > _________________________ > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-teaching@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-sig-teaching _______________________________________________ R-sig-teaching@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-teaching