T Test Z Test Chi Square Test. The chi square test used for testing relationships between categorical values. There are three versions of t test.
It s most common application is in the test statistic following normal distribution where values of scaling terms of test static s are known. There are three versions of t test. The difference between z test and chi square is that z test a statistical test checks if the results of the means of two populations vary from each other.
It was developed by william gosset in 1908 it is also called students t test pen name deviation from population parameter.
The null hypotheses of the chi square say that two categorical variables in the population should be independent. The t test can be said to be the statistical hypotheses test where the test statistic follows the student s t distribution when the null hypotheses is not supported. One of the more confusing things when beginning to study stats is the variety of available test statistics. When you reject the null hypothesis of a chi square test for independence it means there is a significant association between the two variables.
