Predictive forecasting isn't really my specialty. Are you trying to predict sales while you run an A/B test? If so, the best prediction is the average conversion rate. The larger your sample size the more confident you can be in the conversion rate of the variations and the more you could predict if that conversion rate will play out in a couple weeks.

Glad it was helpful!

Glad it was helpful!

Glad you like them and that is great feedback. Thanks.

I hope so too!

Glad you liked it. Hopefully there are more views to come :-)

@@TestingTheory it’s picking up! 😃 4.2K Ps: I love all your videos! They’re super helpful! I am pretty sure it’s going to be raining views soon.

Cause it's your fault

Glad you enjoy it!

Glad you think so!

When you run a test you are keeping back a portion of the traffic that remain in the original experience. Theses visitors see no change to the site. This gives you a point of comparison with your variations where the visitors did see a change.

Yes, the more data you get the tighter your lift intervals and confidence intervals become.

Yeah, I will add that to the list of upcoming videos

Most testing softwares already have a method that they use. If you are using the specific tool then the test isn't as important because you get what the tool uses. If you are looking for an exploration of statistical tests, that wouldn't really fit into a "Statistics Made Easy" video, but is a great idea for a follow up video.

Great summary Paritosh!

Great suggestion!

@@TestingTheory Thank you sir. I hope you can share some of your knwledge here. My specific interest is in KZfaq ads, for example testing various videos but also testing various targeting channels. I can not find any similar information on google at all. Cheers

@@TestingTheory Any ideas on when video A/B testing will be ready? Sorry to bother! Cheers

Yes, the control is part of the test and is your comparison point for the new variations you are testing. The old rate is the conversion rate for the control.

Thanks and welcome!

I'd be happy to connect on linked in and chat there.

Hi Zucethy, the Data Scientist role is a great springboard into doing A/B Testing. Are you doing analysis that might draw conclusions to recommend an A/B test? It might be easiest to convince the company you are working with to test things you are recommended to get causal data. Help them understand that correlative analysis doesn't provide the same value as a/b tests that give you causal data. You could also explore entry level positions for conversion rate optimizers.

Thanks! I'm looking for a job. I had applied to some and got interviewed but they found out I'm lacking of A/B testing experience that had driven conclusions. I was looking for options to learn on my own like Kaggle which gives free dataset to analyse

If you have a testing tool it will do most of what you need automatically. If you want to calculate everything manually in excel or something the formula is pretty complex which wouldn't really fit in a "Statistics Made Easy" video. :-)

Noted

Ha ha. I am glad it was helpful to you

This video is more focused on the statistics "made easy." We could get all technical but it is enough for people to know that a lower p-value is a good thing. Most testing tools don't even show the p-value and most people learning testing don't even need to understand this. We don't need more complexity in testing we need more strategy. I don't think it would have been better if I would have said "P-values are usually found using p-value tables or spreadsheets/statistical software. These calculations are based on the assumed or known probability distribution of the specific statistic being tested. P-values are calculated from the deviation between the observed value and a chosen reference value, given the probability distribution of the statistic, with a greater difference between the two values corresponding to a lower p-value. Mathematically, the p-value is calculated using integral calculus from the area under the probability distribution curve for all values of statistics that are at least as far from the reference value as the observed value is, relative to the total area under the probability distribution curve...." www.investopedia.com/terms/p/p-value.asp

Ha ha. You are right, I think I mixed up my words a little on that one.

What don't you like about the white background? This is the first time I have heard that.