AP Statistics: Understanding Randomness and Simulations
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- Опубликовано: 22 авг 2024
- This video briefly talks about the importance of randomness in statistics and goes over two example of running simulations where we allow numbers to represent random outcomes.
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I really appreciate you. I'm not a very good textbook learner and i never really have been and its not about the reading (i love to read), I'm just more of a visual and auditory learner. So even though you're giving me the same information as the textbook, my brain registers it much better because it's being engaged and and presented like a teacher in a classroom. (Which is hard due to virtual learning). So thank you. - An ADHD Sophomore in AP/DE Statistics
That's great to hear glad they are helping you.
I am back to college and my statistics class has been whooping me, but your videos have been helping me so much! Thanks for putting them up! It works for me even though I am in college cause we use the college version of this book, so even the chapter numbers are the same :)
Wow thanks, this really helped me in my AP Stats class :)
OH MY GOSH THIS WAS SO HELPFUL THANK YOU *cue breakthrough*
So helpful! Understanding this concept more. So when it's "pure chance", it's likely to happen? Thanks.
Thank you
you totally read the book
For step 7, you put that "it will take on average 11 boxes to get all 3 figurines." Where did you get the 11 from?
it's the average of 8,20, and 5: (8+20+5)/3
Really nice! This helped clarify a lot of things, thanks a bunch :3
Thank you so much! This helped a bunch!
this video is awesome ...sensei 🙏
Thank you Master!
Thank you so so much!
it was a nice video helped a lot
thank you so much!
I think when you finished trial 1, instead of taking, 09 you took 95 as next reading. is it ok to do like that.
In the last example, is there a certain amount of trials you should run? It doesn't seem that you have to run an exact amount for that problem, but would there be a general number of trials to run to get an accurate answer?
+Cole Roberts There is no set number of trials that need to be run. In a typical AP problem they will indicate how many to run. Because running some a simulation may take a bit of time I usually ask for 5 or 10 trials. But make sure you understand that the true probability of an event does not reveal itself until the long run, a very large amount of trials. This fact is what the Law of Large Numbers tells us. Thanks for the question!
:D Great help !
on the second trial, shouldn't it have started with 09 not 95 so it would have only taken 3 boxes to get the 3 figurines?
Sorry this reply is so late, but yes you are correct. I think I just had the 0 covered up with my marker writing. However, since the table is random you should be able to start any trial anywhere you want.
in trial 2 it took 20 boxes because you skipped few numbers it may be because of that,
What's happening here? Is this a new way to teach random distribution probabilities? If it is, it's a very strange way to do so. Who's being taught? 2º graders or 3º graders? Let's take the simplest example of this video: 12 men and 10 women are applying for three job positions. Why are you generating possible random sequences? Wouldn't it be more objective and clearer to try to actually calculate the probability of 3 men getting the job (16,23%); 2 men and 1 women getting the job (40,57%); 1 men and 2 women getting the job (33,81%) and at last 3 women getting the job (9,39%). And yes, we could conclude that the fact that 3 women got the job was because they were very lucky or maybe the selection was biased.
@Madeleine Chen I remember seeing this video. But since that happened 2 months ago, I actually had to see it again to remind me of it's content. Wow, I was even more disturbed this time around. In the beginning it points out two things about random selection that makes it fair: 1)- "Don't know the outcome" and 2)- "Equally likely". Well, I have to admit that "Equally likely" nailed it. Actually, that is the true definition and the essence of randomness. "Not knowing the outcome" is redundant and should be ignored when you are already mentioning "Equally likely". The fact is, the more "Equally likely", the more difficult it is to predict the outcome, hence the redundancy. Again, this is a very primitive and unuseful way to predict probabilities. The first example concerning cereal boxes. So we have Brady (62%) , Serena (27%) and Tiger Woods (11%). All you have to do, is apply the same logic used in multinominal distribution probabilities, to conclude that the probability of having three figurines with only three boxes is 11,05%. And four boxes would give you a 22,1% chance of having the three figurines. It is said that a friend claimed getting all 3 figurines with only three boxes. The trials in the video suggest an average of 11 boxes in order to reach the 3 figurines goal. It is explained that maybe someone is lying (being the friend or the cereal company). On the contrary, I would say that the app that is being used in this video is not generating true random numbers, that's why it took an average of 11 boxes to reach the three figurines goal. That being said, I just realized that this video was uploaded 7 years ago. Probably and hopefully, from then till now, things have evolved.
yawn