Pop Pop's strategy with Powerball!

Рет қаралды 39,118

COCCmath

Күн бұрын

Пікірлер: 21

@farrshanise7352 14 күн бұрын

Blessings can I buy that system

@violetsturgill Жыл бұрын

The sunset/night sky/sunrise part was so cute

@COCCmath Жыл бұрын

Yay! That was fun to do. :)

@JES65FLA 20 күн бұрын

Hello, just looking at your previous and future post after this, and still don't see where you have this spread sheet for people to use. Did you state in any of the videos to where to get a copy of it?

@COCCmath 20 күн бұрын

No, because it's not a sheet I distributed.

@MrSunshanmu Ай бұрын

HHi, how can i get this excel sheet please

@maxidaka Жыл бұрын

Thanks for taking the time to compare these strategies in a quantitative manner. I wanted to ask though, Ii you took the opportunity to say double the trial length, Did results ever change in favor of the pop-pop strategy?

@COCCmath Жыл бұрын

Hey there! Thanks for writing, and for the great questions! You can show (using probability) that neither strategy has a *statistical advantage over the other (although Pop Pop's method certainly is easier to fill out the ticket!). The reason I use this problem is so that my students can see how a margin of error can be used to either support or refute statistical significance. Of course, with Powerball, you know exactly how many possible tickets there are (almost 200 million!) so you can enumerate exactly how many winners there are. In research statistics, you have no such luxury, in general - you usually can't enumerate the population. So, you draw a random sample and add a MOE. Your question also made me think of the comparison of practical versus statistical significance: sure, we could run the randomizer as many times as we liked (assuming you had a better CPU than mine!), and, perhaps, one result might show a slight advantage (due to decreasing MOEs with increasing sample sizes). But, again, that's a slightly convoluted strategy - almost like repeating an experiment until you get a result you desire, and then stopping. But! Therein lies the catch-22: in this case, we can show (probabalistically) that there is no difference in the two methods. But that's only because we can exactly enumerate the possibilities. In research stats, you generally *can't...and therein lies the need for controlled, unbiased, replicated experiments: tO tease out what might (or might not) be there, and to analyze the chances that we're wrong. Be well!