Don’t be fooled by randomness. Randomness comes in clumps. For example if you flipped a thousand coins every day for a year and measured how each one predicted the stock market, heads for up, tails for down, at the end of the year you’ll likely have one coin that far out performs the average. But would you use that coin to determine your investment strategy the next year?
And yeah Boeing is now killing people outside of their planes.
Not really. That is just a fact that there’s only 365 days, and the more samples you make increases the odds it’s a sample that overlaps with another (there are fewer unique options).
What the OP is saying is that sometimes randomness can appear less random than other randomness. True randomness will occasionally give results that closely match something non-random. It’s why almost all music players don’t use true random for shuffle. True random you could have the same song play 15 times in a row. In fact, that is expected to happen eventually (assuming infinite time) just as all other sets of 15 songs are.
My dream is for Spotify (and other music playing apps) to let you customize your shuffle algorithm. Minimum number of songs between repeating an artist or album, that sort of thing.
I made a random character selector app for super smash bros that makes you play through every character before it lets you repeat a character. And it won’t let two people play the same character at the same time. My friends and I like playing random characters, but we kept getting the same characters over and over again, sometimes even in the same colors (online only). I got frustrated one day and made the app.
Yeah, true random sucks pretty badly for any sort of repeated selection. You could make your algorithm potentially even better by grouping characters into different roles and not repeating them in a row either. Never give two sword characters in a row if possible, for example.
That’s a really interesting thought. We do still have issues where we get like Ken then Terry (or Mii Gunner then Mii Brawler) back to back, and for people who don’t like that type of characters, its a bummer.
Each character having a list of groups that they belong to, then not allowing players to play a character in the same group consecutively would probably be a huge improvement. I would need to be careful to make sure too many characters aren’t excluded, though. It would be tough to get right, but I think it would be really good.
The birthday paradox derives from how the chance of somebody there having their birthday on a specific day is 1-in-365 (ish)/nr-of-people hence the chance of two people having their birthday on that specific day is 1-in-365^2/nr-of-people, but the chance of two people having their birthday in the same day out of any days of the year is quite different because it’s not a specific day anymore so it’s quite a different calculation (which I totally forgot ;)).
In here the closest to that paradox would the chance of 2 whistleblowers of any company with whistleblowers dying within a few weeks of each other (which, depending on how many companies have whistleblowers, can be quite high) compared to the chance of 2 whistleblowers of Boeing dying within a few weeks of each other (which is statistically a lot lower unless there are thousands of Boeing whistleblowers).
Edit: actually it’s more the chance of any 2 Boeing whistleblowers dying with a few weeks of each other at any point in time (so this includes long after they did it) vs the chance of any 2 Boeing whistleblowers dying with a few weeks of each other during the time they are blowing the whilstle.
The probability of 2 people having the same birthday is 1 in 365 because it’s the same as picking person A’s birthday as a specific day in the year and checking whether person B has their birthday on that date.
Now, the reason the number is so low is that you are basically comparing pairs and with 23 people there are 253 different pairings (23 choose 2 or 22*23/2). With each pair having a 1/365 chance to have the same birthday and having 253 distinct pairs, you would have to fail a 1/365 check 253 times in a row. The formula you can use for the success rate is 1 - (1-p)^x with p being the probability and x the number of trials, so in this case
1 - (1 - 1/365)^253 = 0.5004
In essence, the unintuitive part of the “paradox” is how fast the number of possible pairs grows the more people you add.
Idk if we have any NYJ fans in here, but 2 years ago the coin meme was born. One fan flipped the same quarter every game to predict a win or a loss. It was correct for like the first 7 or so games of the season. It was a pretty wild ride predicting some unpredictable upsets for the jets for both wins and loses.
But given the choice between coins you’d still most likely pick the one that was successful, even if its 99% chance its nonsense - the other coins would have 99.9% (made up numbers).
So out of our analogy, we can’t be sure beyond resonable doubt to arrest Boeing, but a message has clearly been sent to any future whistleblowers
It takes a ton of bravery to be a whistle blower when others aren’t dying like 80 year old diabetes patients. It’ll take even more now, and I hope there are more. Boeing needs to be kicked in the bags.
Crunching the numbers in your example, there’s a 92% chance no coin does better than 55% correct. Randomness happens, but the law of large numbers usually refers to much larger numbers than 1000, and there aren’t 1000 huge companies being investigated right now. I think suspicion is warranted here
Don’t be fooled by randomness. Randomness comes in clumps. For example if you flipped a thousand coins every day for a year and measured how each one predicted the stock market, heads for up, tails for down, at the end of the year you’ll likely have one coin that far out performs the average. But would you use that coin to determine your investment strategy the next year?
And yeah Boeing is now killing people outside of their planes.
That’s a great line!
Finally I have a reliable way of finding my magic stockmarket coin. Thank you kind stranger!
I stole your coin.
You stole the wrong one. Björn Tantau paid me the real one for a bottle of water.
Decoy coin.
Could this be akin to the Birthday paradox?
Not really. That is just a fact that there’s only 365 days, and the more samples you make increases the odds it’s a sample that overlaps with another (there are fewer unique options).
What the OP is saying is that sometimes randomness can appear less random than other randomness. True randomness will occasionally give results that closely match something non-random. It’s why almost all music players don’t use true random for shuffle. True random you could have the same song play 15 times in a row. In fact, that is expected to happen eventually (assuming infinite time) just as all other sets of 15 songs are.
My dream is for Spotify (and other music playing apps) to let you customize your shuffle algorithm. Minimum number of songs between repeating an artist or album, that sort of thing.
I made a random character selector app for super smash bros that makes you play through every character before it lets you repeat a character. And it won’t let two people play the same character at the same time. My friends and I like playing random characters, but we kept getting the same characters over and over again, sometimes even in the same colors (online only). I got frustrated one day and made the app.
It definitely livens up our game nights.
Yeah, true random sucks pretty badly for any sort of repeated selection. You could make your algorithm potentially even better by grouping characters into different roles and not repeating them in a row either. Never give two sword characters in a row if possible, for example.
That’s a really interesting thought. We do still have issues where we get like Ken then Terry (or Mii Gunner then Mii Brawler) back to back, and for people who don’t like that type of characters, its a bummer.
Each character having a list of groups that they belong to, then not allowing players to play a character in the same group consecutively would probably be a huge improvement. I would need to be careful to make sure too many characters aren’t excluded, though. It would be tough to get right, but I think it would be really good.
Didn’t the iPod have the same “issue” that it sometimes played the same song twice in a row or randomly played the next song in the playlist?
You essentially did what Apple did and made the randomness less random so humans think it’s more random.
The birthday paradox derives from how the chance of somebody there having their birthday on a specific day is 1-in-365 (ish)/nr-of-people hence the chance of two people having their birthday on that specific day is 1-in-365^2/nr-of-people, but the chance of two people having their birthday in the same day out of any days of the year is quite different because it’s not a specific day anymore so it’s quite a different calculation (which I totally forgot ;)).
In here the closest to that paradox would the chance of 2 whistleblowers of any company with whistleblowers dying within a few weeks of each other (which, depending on how many companies have whistleblowers, can be quite high) compared to the chance of 2 whistleblowers of Boeing dying within a few weeks of each other (which is statistically a lot lower unless there are thousands of Boeing whistleblowers).Edit: actually it’s more the chance of any 2 Boeing whistleblowers dying with a few weeks of each other at any point in time (so this includes long after they did it) vs the chance of any 2 Boeing whistleblowers dying with a few weeks of each other during the time they are blowing the whilstle.
The probability of 2 people having the same birthday is 1 in 365 because it’s the same as picking person A’s birthday as a specific day in the year and checking whether person B has their birthday on that date.
Now, the reason the number is so low is that you are basically comparing pairs and with 23 people there are 253 different pairings (23 choose 2 or
22*23/2). With each pair having a 1/365 chance to have the same birthday and having 253 distinct pairs, you would have to fail a 1/365 check 253 times in a row. The formula you can use for the success rate is1 - (1-p)^xwith p being the probability and x the number of trials, so in this case1 - (1 - 1/365)^253 = 0.5004In essence, the unintuitive part of the “paradox” is how fast the number of possible pairs grows the more people you add.
That was a great read! Not something I’ve heard of before. Thank you!
And yeah it’s related for sure.
Idk if we have any NYJ fans in here, but 2 years ago the coin meme was born. One fan flipped the same quarter every game to predict a win or a loss. It was correct for like the first 7 or so games of the season. It was a pretty wild ride predicting some unpredictable upsets for the jets for both wins and loses.
But given the choice between coins you’d still most likely pick the one that was successful, even if its 99% chance its nonsense - the other coins would have 99.9% (made up numbers).
So out of our analogy, we can’t be sure beyond resonable doubt to arrest Boeing, but a message has clearly been sent to any future whistleblowers
It takes a ton of bravery to be a whistle blower when others aren’t dying like 80 year old diabetes patients. It’ll take even more now, and I hope there are more. Boeing needs to be kicked in the bags.
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Boeing makes planes not people.
Hey let’s get one thing clear. Planes don’t kill people, people kill people, with planes.
The only thing that can stop a bad plane with a good guy is a good plane with a bad guy.
-idk boeing probably.
Thoughts and prayers 🙏
Crunching the numbers in your example, there’s a 92% chance no coin does better than 55% correct. Randomness happens, but the law of large numbers usually refers to much larger numbers than 1000, and there aren’t 1000 huge companies being investigated right now. I think suspicion is warranted here
You’re saying my intentionally over simplified example to get a point across wasn’t perfect? Amazing analysis…
Do you go by the nickname Captain Obvious with your friends?