No, it actually doesn’t unless you are going on the binary belief that it’s either all bad or all good or you don’t understand significance. The likelyhood of all 5 being bad is low, but no statistician would be comfortable drawing that conclusion that it’s the prevailing norm.
-
-
Replying to @CravenRave @hurricaneross and
Those are the probabilities from *your example*. Look up binomial distribution. (Proof that you don't get probability is that it doesn't matter how many apples are in the bag - the only numbers that matter are the probability of each being rotten and the number you pull out)
1 reply 0 retweets 1 like -
Replying to @CovfefeAnon @hurricaneross and
My example wasn’t there was only 5 bad apples. In a bag of apples that large there’s going to be some non-zero number of bad apples in all probability above 5. Also you should probably use more Bayesian ideas here; there’s an incentive to find bad apples.
1 reply 0 retweets 0 likes -
Replying to @CravenRave @hurricaneross and
You set out an *extremely* simple probability example that's solvable using the binomial distribution and it ... illustrated exactly the point you thought you were refuting There's no "incentive to find bad apples" either - the opposite actually - those are the best apples found
1 reply 0 retweets 1 like -
Replying to @CovfefeAnon @hurricaneross and
Bad apples spoil the bunch comes to mind. Media is encouraged to sensationalize news especially crime stories. You aren’t using the real world in this instance.
1 reply 0 retweets 0 likes -
Replying to @CravenRave @CovfefeAnon and
If you’ve collected a bag of apples, you would want to remove the bad apples from good apples. Also again your ignoring the small sample hypothesis test results
1 reply 0 retweets 0 likes -
Replying to @CravenRave @hurricaneross and
You treat "sample size" like a magic incantation because you don't understand what it is supposed to qualify and when. Probability allows for some very powerful conclusions when *seemingly* improbable things happen often.
2 replies 0 retweets 1 like -
Replying to @CovfefeAnon @hurricaneross and
Wrong sample size bias When the wrong sample size is used in a study: small sample sizes often lead to chance findings, while large sample sizes are often statistically significant but not clinically relevant.
1 reply 0 retweets 0 likes -
Replying to @CravenRave @hurricaneross and
You don't get it. Take *your example* - you can draw exactly the conclusions I stated above - very simple calculations to show each of them. With random 5 draws you can make a very good guess about a distribution. In reality we have way more than 5 draws.
1 reply 0 retweets 1 like -
Replying to @CovfefeAnon @hurricaneross and
You actually can’t. Your hypothesis is most people who commit violent crimes have graduated from low level crimes. Your thoughts on recidivism seem unrealistic.
1 reply 0 retweets 0 likes
No, I'm saying that most people who commit violent crimes have committed a lot of violent crimes and even have often been arrested for them but our system lets off most black criminals entirely until it sometimes eventually puts them away after an especially serious crime
-
-
Replying to @CovfefeAnon @hurricaneross and
Um yikes how can you be so wrong. all data shows Black people are overcharged, oversentenced, and overreprented by the media as criminals. You really don’t know enough to be discussing these things.
1 reply 0 retweets 0 likes -
Replying to @CravenRave @hurricaneross and
It shows nothing of the kind. They're undercharged, undersentenced and by far underrepresented by the media as criminals *compared to how criminal they are in reality* which is insanely more criminal than any other race.
1 reply 0 retweets 2 likes - Show replies
New conversation -
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.