1, t test: mainly used for small sample size (such as n

2.z-test: it is a method used to test the average difference of large samples (that is, the sample size is greater than 30).

Second, the steps are different.

1, t test: establish hypothesis, determine test level α, calculate test statistics, check the corresponding boundary value table, determine p value and draw a conclusion.

2.z test: establish a null hypothesis, that is, first assume that there is no significant difference between the two averages. Calculate the Z value of statistics, and choose different statistical calculation methods for different types of problems.

Third, the characteristics are different.

1, t test: single population t test is to test whether the difference between a sample average and a known population average is significant. When the population distribution is normal, such as the population standard deviation is unknown and the sample size is less than 30, the deviation statistic between the sample average and the population average is T distribution.

2.z test: use the theory of standard normal distribution to infer the probability of difference, so as to compare whether the difference between the two averages is significant. It is also called u-test in China.

Baidu encyclopedia -t test

Baidu encyclopedia -z test