Single Sample T Test Vs Z Test. When to use z or t statistics in significance tests. The student s t test and the z test are parametric tests.
This procedure is more conservative than the z procedure and should always be chosen over the z procedure with small sample sizes and an unknown s. Conclusion by and large t test and z test are almost similar tests but the conditions for their application is different meaning that t test is appropriate when the size of the sample is not more than 30 units. A t test is appropriate when you are handling small samples n 30 while a z test is appropriate when you are handling moderate to large samples n 30.
Many analysts choose the t procedure over the z procedure anytime s is unknown.
The distribution of means one would compute from many different samples from the same underlying population now depends on the shape of the underlying population distribution which must therefore be approximately normal in. To actually do the significance test is we take a sample from the population it s going to have a sample size of n we need to make sure that we feel good about making the inference we ve talked about the conditions for inference in previous videos multiple times but from this we. Proportion problems are never t test problems always use z. Your variable of interest should be continuous and normally distributed and you should have enough data more than 5 values.
