I agree that asking about 2016 donations in early 2017 is an improvement for this. If future surveys are just going to ask about one year of donations then that’s pretty much all you can do with the timing of the survey.
In the meantime, it is pretty easy to filter the data accordingly—if you look only at donations made by EAs who stated that they joined on 2014 or before, the median donation is $1280.20 for 2015 and $1500 for 2016.
This seems like a better way to do the analyses. I think that the post would be more informative & easier to interpret if all of the analyses used this kind of filter. (For 2016 donations you could also include people who became involved in EA in 2015.)
For example, someone who hears a number for the median non-student donation in 2016 will by default assume that this refers to people who were non-student EAs throughout 2016. If possible, it’s good to give the number which matches the scenario that they’re imagining rather than needing to give caveats about how 35% of the people weren’t EAs yet at the start of 2016. When people hear a non-intuitive analysis with a caveat then they’re fairly likely to either a) forget about the caveat and mistakenly think that the number refers to the thing that they initially assumed that it meant or b) not know what to make of the caveated analysis and therefore not learn anything.
I agree that asking about 2016 donations in early 2017 is an improvement for this. If future surveys are just going to ask about one year of donations then that’s pretty much all you can do with the timing of the survey.
This seems like a better way to do the analyses. I think that the post would be more informative & easier to interpret if all of the analyses used this kind of filter. (For 2016 donations you could also include people who became involved in EA in 2015.)
For example, someone who hears a number for the median non-student donation in 2016 will by default assume that this refers to people who were non-student EAs throughout 2016. If possible, it’s good to give the number which matches the scenario that they’re imagining rather than needing to give caveats about how 35% of the people weren’t EAs yet at the start of 2016. When people hear a non-intuitive analysis with a caveat then they’re fairly likely to either a) forget about the caveat and mistakenly think that the number refers to the thing that they initially assumed that it meant or b) not know what to make of the caveated analysis and therefore not learn anything.
The median 2016 reported donation total of people who joined on 2015 or before was $655.
We’ll talk amongst the team about if we want to update the post or not. Thanks!