3 ms·
You demand, eh? Honestly, really, truly, honestly, i never bothered with p values as a statistician except for two cases. The first is when performing a test f
by hessenwolf 16y ago
You demand, eh?
Honestly, really, truly, honestly, i never bothered with p values as a statistician except for two cases. The first is when performing a test for somebody else to go into a standard article format. The second is when automating reports on complex data.
P values are for people who you do not trust to make decisions. Graphs and arrays of summary statistics fro. Several differentodels are for statisticians.
Also, i disagree that model choice will be overwhelmed by the data.
- tel 16y agoHah, I should really write these with more care. I'd feel entitled to demand, but more meekly expect that there's a bit more trust and convention in scientific publication. Though that can be taken too far. You're right that model choice can still break your analysis given large amounts of data. I was thinking more in terms of a whole inquiry where large amounts of data will help you to locate a model that extracts the maximal information from your observations. If we're able to keep experimenting forever, we pretty much assume we'll eventually get highly accurate maps of the world. The primary difference was in utility functions where no matter how long you experiment they remain exogenous and static.