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When would you use a two-sample test?
You can use the test when your data values are independent, are randomly sampled from two normal populations and the two independent groups have equal variances.
What is a two sample z-test?
The z-Test: Two- Sample for Means tool runs a two sample z-Test means with known variances to test the null hypothesis that there is no difference between the means of two independent populations. This tool can be used to run a one-sided or two-sided test z-test. Two P values are calculated in the output of this test.
Is there a two sample test for a continuous distribution?
It looks like it only provides a two-sample test for a continuous distribution: If y is numeric, a two-sample test of the null hypothesis that x and y were drawn from the same continuous distribution is performed.
How to do liklihood ratio test with discrete data?
If you know what distribution the data comes from (or at least are willing to assume a distribution) then you can do a liklihood ratio test on the equality of the parameters (compare the model with a single set of parameters over both groups to the model with seperate sets of parameters).
How to test the null hypothesis of a continuous distribution?
If y is numeric, a two-sample test of the null hypothesis that x and y were drawn from the same continuous distribution is performed. Alternatively, y can be a character string naming a continuous (cumulative) distribution function (or such a function), or an ecdf function (or object of class stepfun) giving a discrete distribution.
Can a discrete distribution be a character string?
Alternatively, y can be a character string naming a continuous (cumulative) distribution function (or such a function), or an ecdf function (or object of class stepfun) giving a discrete distribution. In these cases, a one-sample test is carried out of the null that the distribution function which generated x is distribution y ….