equal_var value of scipy.stats.ttest_ind interpreting the result of a null hypothesis AB test

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I am trying to interpret the results of a null hypothesis A/B testing by conducting a two-sample t-test and I am using scipy's stats.ttest_ind function.

ttest_ind function has a parameter called "equal_var" of a boolean type. When this is true (default), this seems to assume that A and B follow the same variance.

In the case of a null hypothesis A/B testing, should this be set to True or False? Also, how does this parameter change the formula? Not so sure this is the right forum for this type of question.

Thank you in advance!

scipy.stats ab-testing
1 Answers

TL;DR: if you want to be safe use equal_var=False

Here you can find elaborate answers to the question why not always using the Welch's t-test (equal_var=False). Admittedly, there you can find arguments for both side but only academic references in favor of using Welch's t-test. On Wikipedia it is argued in the same direction: if variances are unequal, you want to use Welch's t-test, if they are not you are still safe.

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