In the statement we have the T test, Mann-Whitney test, qui-square x² test and variance analysis (ANOVA) which are statistical tools.
Mann-Whitney Test Suitable for comparing two groups not paired to verify whether or not they belong to the same population, when the test is not possible to apply T.
T Test T Suitable to determine the statistical difference between two samples not paired.
Test Analysis Variance (ANOVA) Suitable to determine if the average of three or more groups are different using F
qui-square Suitable to evaluate the association between two qualitative variables x and y.
to compare the averages of two samples , which can be The same set of individuals where the values were taken before and after treatment we use the T as a hypothesis test. In addition, this test should satisfy the conditions that the variable is quantitative, the variable has normal distribution and the sample should a normal distribution.
If we have the same situation , however, the groups have no normal approach, then we should use the non -parametric test test Mann-Whitney .
Already when we want to compare the result of samples with qualitative variables with a pre-established standard we use the x² qui-square test . This test satisfies the conditions of the variable being qualitative and the results presented in a contingency table with the observed proportions.
We call Variance Analysis (ANOVA) when we compare quantitative variables of two or more Treatments, that is, several experimental groups.