Recent submissions

Comment · 12 years ago
Yes! This is very important to us in dealing with transactional email.

Our Z-Test Method in Confidence.js pinpoints when results become statistically significant by calculating the required sample size at any given time using the standard error, zScore, and margin of error. If we have more samples than required, we can stop our test with confidence that we have statistically significant results.

We're still working out a way to do this with the new method - we have a hunch it might have to do with identifying when the confidence level becomes stable (as it does with more samples over time).

Comment · 12 years ago
Thanks for your question! I'll pass it on to Emily, our stats expert.
Comment · 12 years ago
Hey! I'm the author of Confidence.js. Emily Malcolm and I have been working hard on this new approach for the past few weeks and we're super excited to share it!

We're both here to answer any questions :)

Comment · 12 years ago
Hey martian, thanks for the feedback. Your methodology is pretty sound - it looks like we use a similar technique. If you supply a small sample size here, you'll get the message, "There is not enough data to determine a conclusive result".
Comment · 12 years ago
The recommendation of 95% significance level is quite common across A/B testing resources. The main goal here is to be able to say which variant will consistently perform best (in this case, 95% of the time).

I agree that it would be useful to be able to change the confidence level based on a site's specific needs - this is a feature I am looking to implement in Confidence.js soon.

Comment · 12 years ago
Hey Noel,

I was in charge of the math here - I really appreciate your feedback. You seem really knowledgeable in this area and I would love to improve this A/B testing library.

If you have some time to chat, email me at [email protected]

Comment · 12 years ago
This is a feature that I would love to add to Confidence.js sometime in the near future.
Comment · 12 years ago
Hey, I'm the author of Confidence.js which was used to power this A/B testing calculator. That sounds really interesting and worth looking into - thanks for the feedback!
Comment · 12 years ago
You're right about revenue being a very important metric, and I think optimizing for conversions has its place too. I would be interested to hear the results of your repurposing!
Comment · 12 years ago
Glad you like it, happy to have you contribute :)
Comment · 12 years ago
Comment · 12 years ago
Hi sharnett,

Thanks for bringing that to my attention - I agree that our explanation is a little more convoluted than it needs to be. I'll update that later today to be more "readable" ;)

Comment · 12 years ago
Thanks for the feedback!

Confidence.js comes from how we operate on A/B tests at sendwithus - we think of them as variants associated with results. While the code could definitely boil down to a few simple math functions, we find objects to be a good way to organize our data models.

Comment · 12 years ago
Hey! I'm the author and I'd be happy to answer any questions you might have.

Confidence.js is based on the A/B testing code that we use at sendwithus.

A/B testing math is hard and we've worked really hard on making this great. Let us know what you think!

Comment · 12 years ago
The layout generator is so cool! Yoink.

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