|
|
|
|
|
|
by blauwbilgorgel
4404 days ago
|
|
|
A/A testing (Null testing) or A/A/B testing gives a different effect than A/B testing. Microsoft Research suggested (http://ai.stanford.edu/~ronnyk/2009controlledExperimentsOnTh...) that you continuously run A/A tests alongside your experiments. An A/A test can: - Collect data and assess its variability for power calculations - test the experimentation system (the Null hypothesis should be rejected about 5% of the time when a 95% confidence level is used) - tell if users are split according to the planned percentages |
|
|