Science

I can't say that. The guy doesn't believe in aliens. Seriously, how smart could the guy be ?

I'm almost positive that Neal degrass tyson has a thing on YouTube covering this exact scenario.

I myself would side with whatever that guy says.

"To put it another way, for every 30 flips of a coin, about 15 will be heads."

No. If you do enough flips of a fair coin - and by enough, I mean a significantly larger number than 30 - the average will be about 15 heads to each set of 30 flips, which is not the same thing as "for EVERY 30 flips." VA did your math for you, so you already know that getting 15 heads on 30 flips doesn't happen 72% of the time.

<p>"<span style="color:rgb(0, 0, 0); font-family:open sans,sans-serif; font-size:14px">But it's no accident that multiplying 1/15 by 30 gives you the same answer."</span></p>

<p><span style="color:rgb(0, 0, 0); font-family:open sans,sans-serif; font-size:14px">And that is how I got my answer. Run a simulation and the answer will be 2.</span></p>

<p><span style="color:rgb(0, 0, 0); font-family:open sans,sans-serif; font-size:14px">From Wikipedia:</span></p>

<p><span style="color:rgb(0, 0, 0); font-family:open sans,sans-serif; font-size:14px">Law of large numbers: "</span>In probability theory, the law of large numbers (LLN) is a mathematical theorem that states that the average of the results obtained from a large number of independent and identical random samples converges to the true value, if it exists."</p>

<p>"For example, a fair coin toss is a Bernoulli trial. When a fair coin is flipped once, the theoretical probability that the outcome will be heads is equal to 1/2. Therefore, according to the law of large numbers, the proportion of heads in a "large" number of coin flips "should be" roughly 1/2. In particular, the proportion of heads after n flips will almost surely converge to 1/2 as n approaches infinity."</p>

<p>To put it another way, for every 30 flips of a coin, about 15 will be heads. </p>

@8... That quote you posted was by a Snowflake MAGA Cult member.... Who has me blocked, yet writing my name in the post. I'm selling my house and just live in their head year-round.

I'm not sure who you are talking about with that but it appears to be me... I don't have you blocked?

Well, we know one of the ways that poster is probably gonna check out.

It's my anti nursing home strategy.

Well, we know one of the ways that poster is probably gonna check out.

“If I drink 15 beers in a day. I will come on here and say something that will piss off Gumby and 8.”

This quote makes my liver hurt.

That quote you posted was by a Snowflake MAGA Cult member.... Who has me blocked, yet writing my name in the post. I'm selling my house and just live in their head year-round.

“If I drink 15 beers in a day. I will come on here and say something that will piss off Gumby and 8.”

You’re not giving yourself enough credit. You do it with zero beers.

Well, I can't answer for how he's arrived at the answer of 2 hits out of 30 being the average outcome.

But it's no accident that multiplying 1/15 by 30 gives you the same answer. Just like if it were 1/3 in 60 tries, the average will be 20.

The reason is because the "expected value" of an outcome is the probability of that outcome multiplied by the "value" of it. Just like lottery ticket bought for $1 when the odds of winning are 1 in 100 million, but the jackpot is 200 million, has an expected value ("average") of $2. (This is ignoring multiple winners and intermediate prizes). Yeah you're almost always going to be lose your $1, but the average outcome is $2. The median outcome will be $0.

Anyway.. I dont see a reason to beat this to death any longer.

Put another way, flipping a fair coin 30 times and getting 15 heads has a probability of only 0.14446. It goes up to 0.57223 if you change the terms (I'm using a coin flip calculator for the math, but it looks right) to "at least 15 heads" and down to 0.42777 for less than 15 heads. But Wayne thinks it's a straight line calculation with some wiggle room, which isn't how probability works.

The coin flip calculator only goes out five places, so it comes up with 0 probability of 30 heads in 30 tries, but that's not true. It's tiny, but not zero. Wayne's view doesn't allow for that.

It's not poor word choice: "And that works out to twice a month on average. So ggmm, you agreed with me. It is right there in your post. You have a 1 in 15 chance per day to win. One day does not depend on the next. 1/15 is .066667chance. Multiple that time 15 and it is about 1 (Once every 15 days). Multiple it by 30 and it is about 2 (twice out of 30 days).

Flip a fair coin every day and about half the days will be heads, so on average you get 15 heads every 30 days."

But you don't. There's distribution in probability, but not like that.

I read him saying it works out to twice a month on average. If he said otherwise somewhere else, I don't know.

I've seen Wayne make some wacky claims when it comes to science. But as far as anything I've seen him say on this specific issue, I'm of the belief that this confusion is at worst a result of poor choices of words.

No. He doesn't understand independent probability. Which is why he keeps saying if you do a thing with a probability of 1/15 for 30 days on average you will get the thing twice.

Yeah I should have just used an asterisk.

Normally I would use a • sign (CTRL-0149). But I don't think it'll render properly here.

Holy shit it did.

"...is not the same as twice in 30 days"

Right. I said that was the average expected outcome in 30 tries. Every event is an independent probability.

That's what I understood Wayne's statement to mean.

It's been a long time since I had to deal with probabilities and statistics, but the sad part is I followed VA's equations- except for the "@" part. Back in my day we used an asterisk instead of an "x" to indicate multiplication, I've never seen @ being used. No matter...

Now I'm wondering what the equation to indicate the probability that Paris (the one in France) exists looks like.

Love the way ya think 2 lol

This: "The answer is 2. Yes, it'll only actually BE 2 28% of the time..."

...is not the same as twice in 30 days, even if you're saying approximately to cover the inexactitude. Probability distribution is a real thing, but each time, if the odds are 1/15, they stay 1/15.

Since you're following the math, Wayne, I'm really unclear as to why you can't follow the logic, wherein 72% of the time it won't be 2.

here's one for all you science guru's...how do you deny the science on the devices you are using to deny science....every cut and paste you claimas yours...the science to allow the cut and paste and the science in x o's to decode your cut and paste...see where this is going...all science in everything thing we do including flushing your toilet!

"I'm not sure if that's a probability thing or a scientific well documented FACT."

Some things can feel like a probability distribution when they're really just cause and effect. ;)

<p>Thanks <a href="https://www.swinglifestyle.com/profile/lookup.cfm?usercode=18667678">vabeachcouple33</a>,</p>

<p>I'll have to refresh myself on binomial distribution. I think that shows what I am talking about better than I am wording it. I know that it isn't going to be exactly 2 every month. That is why I said 'average'. I think you left out a closing parentheses in your fromula. I had to add one. :) But I learned something. I didn't know you could do MAX(A:A). I would have done MAX(A1:A31).</p>

Here's one for you scientists.

If I drink one beer a day. I will quietly go about my business.

If I drink 15 beers in a day. I will come on here and say something that will piss off Gumby and 8.

If I go past 15 in a day, even TBR will chime in.

Of course now that I think about. I'm not sure if that's a probability thing or a scientific well documented FACT.

As for the formula for the binomial distribution... Best I can do on this site... I'm choosing to use an @ sign instead of multiplication to avoid confusion with x, so sub that out. Let's go with the odds of 3 hits out of 30.

P(x) = [n!/((n-x)!x!)] @ p^x@[(1-p)^(n-x)]

Where:

x = number of "hits" (in this case 3)

n = number of trials (30)

p = 0.066666667 (1/15)

P(x) = [30!/((27)!3!)] @ 0.066666667^3@[(0.933333333)^(30-3)]

P(x) = [24,360/6] @ 0.066666667^3@[(0.933333333)^(27)]

P(x) = 4,060 @ 0.000296296....@0.15523618....

The answer is 0.18674... 18.67%.