Single Sample T Test Vs Z Test. Proportion problems are never t test problems always use z. 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.
Z test is used to when the sample size is large i e. Differences between z test and t test z test is the statistical hypothesis which is used in order to determine that whether the two samples means calculated are different in case the standard deviation is available and sample is large whereas the t test is used in order to determine a how averages of different data sets differs from each other in case standard deviation or the variance is not known. Your variable of interest should be continuous and normally distributed and you should have enough data more than 5 values.
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.
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. Differences between z test and t test z test is the statistical hypothesis which is used in order to determine that whether the two samples means calculated are different in case the standard deviation is available and sample is large whereas the t test is used in order to determine a how averages of different data sets differs from each other in case standard deviation or the variance is not known. Z test is used to when the sample size is large i e. 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.
