We've collected another data point. A win with pocket 3's. He's now at 22 out of 56 with a p-value of .07.
There's been a lot of good posts. Thanks for all the input. Here are my thoughts.
He is biased since he is the one asserting the hypothesis you are testing (that the results are due to his unluckiness).
Hmmm. This may be our point of misunderstanding. He isn't asserting the hypothesis. It's more like he's trying to determine if his observation is accurate. He doesn't actually believe in luck. But he's having a hard time what he perceives as a consistent bias in his hands.
And I said what has not been eliminated is the possibility of that bias corrupting data collection.
Sure, it can. He might even be deliberately lying. When he first told me about what he was doing and I computed the probability of the result, which had a p-value
between 5 and 10% for a small sample (clearly insufficient), I had to admit that he might have a point.
And neither side is consciously cheating. That's the nature of bias. It really isn't the same thing as fraud. It often clouds our perception, which is why hypothesis testing should do its best to eliminate or minimize its influence.
I familiar with sheep and goats. My husband, however, is far more of a goat than a sheep. More to the point, that explanation doesn't help
him understand what is going on so it's off the table. You, of course, are free to make that assumption. There's no reason that you should trust his data or take my word about it.
Again, the word "luck" is ambiguous. I think the distinction here is that you (or the person you're responding to) is using "experienced a long streak of bad luck" in the non-explanatory sense. It's just a synonym for "chance" and is no more meaningful that observing that he lost more often than he won.
On the other hand, I think "someone is unlucky" is here being used in the predictive/explanatory/causation sense--luck as some force other than random chance responsible for the outcome observed.
I've been saying this over and over, but people still want to conflate these two usages and it leads to the confusion you've run headlong into.
I'm actually comfortable with using it both ways simultaneously. I don't see how attributing an extremely unlikely outcome to random chance is distinguishable from considering luck a predictive/explanatory/causative sense in this situation. Nor do I especially care to try at this point. We haven't yet reached a sufficiently large sample to draw a firm conclusion one way or the other, so it may not be necessary.
Now, back to your study. If you specify a number of trials and a confidence interval (that's part of the hypothesis), and find at the end that you have a result statistically significant from random chance, I still think it's not reasonable to accept the hypothesis that the outcome is due to his being unlucky. (Again, we're talking about causation, not just description. If it were merely description, then there is NO difference between the hypothesis you're testing and the null hypothesis.)
I think it would be far more likely that something was wrong with the methodology or analysis. (Most likely, the probability of each trial wasn't actually 1:2, or there was some error in data collection, or something else relatively mundane.)
Yes, as I said, that was my first suggestion. But having taken the data himself, he is understandably unwilling to accept that. So he has continued to collect data. I can understand your feelings regarding accepting the hypothesis of causative luck. However, if the trend continues it does confirm that his observations have been accurate.
We collect data. All the data can potentiallyshow is a long, statistically anomolous streak of bad luck. It seems reasonable to me to conclude that someone who experiences that is unlucky.
What is the difference you perceive between the two? How would you prove someone is 'unlucky' versus showing that they experienced a long streak of bad luck?
I would say that a repeatable and significant demonstration of 'bad luck' would be worth examining further.
Yes, it does seem worth examining. Which is what we in the process of doing. We are not yet to the point of being able to claim with certainty that it is, indeed, happening.
In much the same way that someone who said they could predict the roulette wheel, or the tumble of craps dice with a significant and repeatable level of accuracy over the mathematic expectation.
Yes, that would be worth examining as well. Are there professional gamblers who earn a living playing roulette? I don't know if there are or not, but I presume not since it's a game of luck not skill. Is that correct?
As Beth has stated, there is no interest in looking at how this perceived 'luck' is impacting the bottom line, nor any interest in improving the game, so its immaterial.
Sorry, but that isn't why I opened this thread.
I have to agree with Beth here: The claim of "being unlucky in poker" only makes sense if "luck" is something supernatural. So it wouldn't work in a lab setting. (Or at least it might not.)
The lab setting is perfectly okay to analyze random chance fluctuations - but we don't need a lab for that, since we know what will happen, right?
Yes, exactly!
@Beth: I'd be interested in seeing the actual stats, if it's not too much work. Unless the losing overcards tend to include an ace and a king, my idea is rubbish either way.
PM me your email and I'll send you my Excel file.
Perhaps - but Beth's data are gathered from two very different sources: Online 'free' games (I don't know if multiple online sites are involved) - where I think for very good reasons, it is highly implausible that tells would make a hill of beans difference for these sorts of hands.
Only one on-line site. And he says only about 4 of the hands were from his rl games, so less than 10%. He also tells me that all the on-line poker sites are now shut down completely, so his data collection experiment may be over.
You would need to analyze both subsets of data separately (live game vs free online play) and you would need to know a good deal more context: Are the players the same game after game, does Beth's husband apply these sorts of principles to his game & keep notes (even mental ones) on the proclivities of the other players?
The players vary with some people there fairly consistently and others may only come once or twice. I've no idea how good they are, but they all have day jobs. Nobody there is earning a living at poker.
...So - that the effect is of nominal 'value', and the likelihood that in the sample we're seeing so far, that Beth's husband has been able to influence meaningfully these results as a result of the 'reading' skills described is pretty remote.
I agree.
True. (unless whichever entity was responsible for the luck and bad luck decides it doesn't want to be tricked by a test-game, of course ...)
That Loki is such a card! I hear the coyote is a trickster too.
