In statistics there are 2 type of errors. A type I error is a false positive (believing something is true when it’s false), whereas a type II error is a false negative (believing something is false when it’s true). Depending on what kind of error you want to make it’ll influence how you approach and make decisions.
Specifically, these 2 types of errors are very relevant to game selection. When you’re deciding whether to add in a tournament to your schedule the most* basic question you’re asking is “Am I +EV in this game”. The null hypothesis, or the base assumption, is that you’re -EV. Meaning you need evidence that you’re +EV to disprove the base assumption.
If you misinterpret the evidence and think that you’re +EV in a tournament when you’re -EV then you’ve made a Type I error. Meaning you’ll play a MTT where you’re -EV.
If you misinterpret the evidence and think that you’re -EV in a tournament when you’re +EV then you’ve made a Type II error. Meaning you’re skipping a MTT in which you’re +EV.
Generally, if you’re conservative in your game selection you should be trying to minimize your Type I errors and setting a higher bar to prove that you’re +EV in a tournament.
Whereas, if you’re aggressive in your game selection you should look to minimize your Type II errors, and setting a lower standard of proof that you’re +EV in a tournament.
There’s no right answer when considering which way to go. Committing the Type I error will put you into -EV games and drastically increase your variance and lower your ROI, committing the Type II error will leave money on the table.
You decide.
[Edited by SDK1987]
