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Does this Make Sense to Anyone? (6)

10-27-2011 07:42 PM #1 vuedoolor (Member)
Does this Make Sense to Anyone?

http://www.buildinganempire.com/poisson2.html

I feel like I can almost understand it. Need commoncraft to come explain this but for those nerds out there who understands this, it may be useful for you guys.

Why am I posting this? I have no idea

10-27-2011 07:50 PM #2 izmb (Member)

What's so confusing?

10-27-2011 09:14 PM #3 polarbacon (Moderator)

the answer is 42

10-27-2011 09:47 PM #4 allthegold (Member)

I highly encourage you to read this a few more times to make sure you understand it. Stated as simply as possible, the formula gives you a probability or distribution of probabilities that a number of events (signups) will have occurred in a large number of opportunities for said events to occur. I imagine that you'd be using it to see how likely a number of conversions would be, given assumed conversion rates on a large set of views or clicks.

Here's the most important part of the article:

How to use it: There are many ways that you might be able to use the Poisson Distribution in a useful way. Say you join a new webmaster program and you need to convert it at 1 in 1200 for it to be useful to you. You send 1200 visitors and want to know whether that is enough to have fairly tested it. From the example above, you know that you will get 0 out of any random 1200 37% of the time, a fairly large occurence, so you really need to stick it out a little longer.

How about if after 3600 visitors sent you still don't have a signup? You are still wondering whether you have sent enough traffic to have given it a fair chance. What are the odds that you will have gone 0 for 3600 by chance if the program is going to convert 1 in 1200 for you overall? Here you expected (needed) to have 3 signups (3600/1200) so m is 3. The case you are interested in is for x=0.

Probability = (e^-m) * (m^x) / x!
Probability(x=0) = (e^-3) * (3^0) / 0! = .05
In other words, in 5% of the cases where we look at any random set of 3600 visitors, we will have 0 signups. It's not impossible that you might end up doing 1 in 1200, but the odds have slipped pretty far by then.
There are TONS of applications for this, but the most common way affiliates will use it is in determining if a test is conclusive or not. If you're depending on 1 in 1,000 people to convert, simply getting 1,000 unique visitors will NEVER let you know with any certainty if the offer is profitable in the long run. The smaller your estimated conversion rate is, the more important this idea becomes.

Edit: Use this once you understand the idea behind it: http://www.anesi.com/poisson.htm

10-28-2011 05:31 AM #5 vuedoolor (Member)

yeah I played with that calculation thing and now understand it better plus I had to reread the article LOL

10-28-2011 05:00 PM #6 tijn (Moderator)

nice article. saved in instapaper for reading tonight

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