Generally, with sample sizes that are smaller, if you know the population deviation, then you can use a z distribution, however if the population deviation is unknown and you are using the sample deviation, then the t-test is more appropriate
When working out confidence intervals based on population samples are you supposed to always use t-distributions, standard normal (z) distributions, or do you make a choice based on the sample size?
Up until now I've been lucky enough to have large sample sizes (for some work I'm doing) so have been using the z-distribution. However I now have some data sets which range from n=1 (lol) to n=29 so am not sure if I should now be using t-distributions to define confidence intervals, or how I'd make that decision (e.g. use t-distribution if n<30, for example?)