Are you conducting some kind of experiment, or planning to? Well, I don't know about it yet! So when the stunning results come out, I can say "hey, maybe you just got lucky. If your experiment had returned a negative result then we wouldn't have heard anything about it".
This is called publication bias.
So I'm launching the anti publication bias registry, a place to record EA-related experiments before you know what the results are going to be.
It's on a wiki, which allows you to change the description afterwards - this has good points and bad points. A good point is that it allows you to change your experimental design as you go along, in order to best fit the world. A bad point is that this can introduce bias. But remember, we do have the edit history so blatant cheating will be hard (such as completely changing an experiment, or deleting it). More subtle cheating is also discouraged, such as adding extra statistical tests because the data seem to be pointing that way.
You can also register experiments by commenting on this post - someone will probably copy it to the wiki eventually anyway.
Be as detailed as you can be bothered to be in your experiment descriptions. This will hopefully encourage others to follow your example and be careful in how they set up their experiments.
A second purpose of this is to introduce social commitment towards actually completing and writing up experiments once they've been suggested.
Have fun doing science!
I had a look at the current entries, and it's a bit unclear to me. For the facebook welcome, I don't understand the methodology. Are you comparing different standard greetings against each other? If so, how do you decide which greeting gets used for which person?
In general the idea with pre-registration should be to state up-front exactly what questions you are trying to answer. This is a non-negligible amount of work involved in doing this properly; this is the cost of pre-registration (and why it isn't a total no-brainer, particularly early on in a field when exploration and hypothesis generation is more important than hypothesis testing). Of course bringing down the cost helps make it worthwhile earlier.