Timeline for simple random sampling and in-group comparison
Current License: CC BY-SA 4.0
6 events
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| Jul 3 at 11:35 | comment | added | BenP | Further, you explain what you DO want to test and what NOT. But for me, I'm not an expert in AB experiments, more explanation is needed to better understand the two different things you mention. They sound really similar to me (as a layman), and my wife btw :-) But as you frame it now, I do not think it is possible to extract what you are looking for from the data you have. | |
| Jul 3 at 11:26 | comment | added | BenP | @Iman The added PS in your question is an important one! You say "... increase or decrease ... is due to the UI change and not because the new UI caused users to change their original purchase intentions?". Because you have two DIFFERENT groups of visitors, and each visitor is observed only once. So strictly speaking you do not observe increase or decrease of behaviour over time, but only differences between the two groups of visitors, which can be statistically tested (chisquare test, mulitnomial regression ...) . But the PS suggests a different problem. | |
| Jul 3 at 2:28 | comment | added | Iman | My primary concern is ensuring that any observed changes in purchase behavior are due to the UI change itself and not because the UI change influenced users to switch plans. Specifically, how can we be sure that an increase or decrease in purchases for Plan A, for instance, is due to the UI change and not because the new UI caused users to change their original purchase intentions? | |
| Jul 2 at 18:27 | history | edited | BenP | CC BY-SA 4.0 |
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| Jul 2 at 18:22 | history | edited | BenP | CC BY-SA 4.0 |
added 196 characters in body
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| Jul 2 at 18:16 | history | answered | BenP | CC BY-SA 4.0 |