I'm in college now and have been watching videos from this channel since high school. Needless to say, they've been so helpful. So crazy and great I can find a resource as great as this on RUclips!
taking 4000 level biostatistics and this is much more effective, and efficient, explanation of hypothesis testing! I feel like I wasted hours reading a book that is written in archaic jargon, when everything I needed to understand the logical concepts is right here.
*_...sometimes statistics talks so slightly about usability, that it looks offtrack from any-use-at-all (mathematics isn't to blame)-When I consider votation outside the entropic zone of indistinguishability from random-voting, I include the likelihood of rejected results being returned for a specific reprocessing (e.g. contested Laws returned to the Supreme Court whose workload is fixed), and I perhaps-arbitrarily for otherwise-general use select σ√2π as where the 'Normal' bottoms-out..._*
Ytterbium-171 atomic clocks demarcate a second with their transition frequency of 518, 295, 836, 591, 614 (518 trillion and change), with an Allan's deviation of 10^17! And you thought that you had control over your p.
Echoing the comments about food...Food serves as a such a perfect source of relevant and manipulatable examples for a stats course. Three thoughts: 1) She does a great job using food in just this way in every one of the videos I've watched so far (up through 21) 2) People with eating disorders should look to Khan Academy for their video-based stats ejumukashun. Though inferior to CC in myriad ways and overall, at least his chicken scratch drawings and overly assumptive examples in no way resemble something comestible. His videos rival unadorned chicken breast in blandness and enjoyability. CC videos, well, chicken parm baked by a Neapolitano grandma named Maria! 3) She's an obvious plant by the Koch brothers and big-ag.
Could you please talk about effect size. And if it’s as important as statistical significance. Especially with complete population stats (like census). So we divided the us population into males and females, can we use effect size?
No. You should expect statistically significant findings to be incorrect more than 5% of the time, because statistically insignificant findings are very rarely reported. Also keep in mind that you can sample your population 20 times, for which you can expect 1 significant finding. To counteract this, you correct for multiple testing by controlling the family wise error rate or false discovery rate.
I used program to generate a normal curve stated in last problem with mean of 2300 and SD of 500/sqrt(60) to get p value of 12% and not 18% as said in the video. CC please expaln?
You take a look at the distribution of your null hypothesis and calculate the area under the line from the value of your test statistic towards infinitely more extreme. The area under the the line of the entirety of your null hypothesis distribution should add up to exactly 1, thus the area that you are calculating for your statistic has to be smaller than 1.
Can someone explain to me this conclusion 8:08 ? : I understand that 9% of mean caloric intake are higher than 2400. And that since the distribution is symmetric, 9% higher than 2300 is 9% lower than 2300. But how does they add up ? WHY THE HECK do we care to use the symmetric rule to say that 18% are away from 2300. Where does 2400 fit in this conclusion ??? I need help seriously y_y
The p-value is the probability of the data randomly occurring. If the p-value is high, then the data is considered not significant and you fail to reject the null hypothesis. If the p-value is low, then the data is likely not random and you have statistically significant data (you fail to reject). The p-value for this problem is .09, while the standardized p-value cut off in statistics is .05. In this example, the probability of the data randomly occurring is 9%, so we can't say the data is significant since the probability greater than 5%.
@@freezerburnfreeze Thank for you answer although that is not what I wanted to understand, I actually do understand well the p-value but I don't get how a two sided p-value work in this example. They use the symmetric rule but it is not the logic behind it that I don't understand, it is how do they manage to use it here that is not clear.
In this case, the question is whether people with gene X eat a different amount of calories than the general population (NOT whether people with gene X eat HIGHER amount of calories). Although we got the information that the mean of a sample of 60 people with gene X is 2400 and is greater than the mean of general population which is 2300, the mean of the all the people with gene X might be smaller or greater than 2300, so we need two cutoff numbers on both sides to decide whether to reject NHST and it's .025 for each side, and comparing .09 to .025 is just same as comparing .18 to .05.
I'd really like to love this series, like the many excellent other subjects, but it doesn't quite have the same flair. Disappointing to see logical contradiction compared to unlikely.
You say that the current consensus is that alpha should be 0.05 - this is standard in the social sciences. But ask a physicist? When they found the Higgs boson they went out 5 standard deviations from the null hypothesis mean.
I hate to nit-pick, but your examples misused standard deviation. 175 spots with a standard deviation would have a bell curve MUCH wider than what is shown. The bell curve shown has a mean of 175 with a standard deviation of approx 11 or 12. Please make your graphics match your examples.
the graphs in this example use the standard error, not the standard deviation since it's the mean number of spots for a group of giraffes not just one!
She could not have been more unclear in her definitions and examples. She literally made it as complex and confusing as possible even though this concept is actually not so.
There are so many things wrong in this video I can’t even start to describe. Just get a statistician to take the show and correct the misconceptions, please.
Stating that chance alone cause a test to be wrongly significant and use of hard cutoffs are the most common and dangerous misconceptions here. Just read the ASA statement about p-values (February 2016 if I remember correctly) which talk about these issues.
@@BernardoPowaga There is a whole episode in the serie about that p-value "standard" discussion and the reproductibility crisis in sciencitfic research, tho. And she does mention the ASA statement and provide a link to it.
Most useful CrashCouse episode of all-time for academics and scientists
truer word have never been spoken
only 100k views a year later, I guess we are going extinct
As someone who is studying statistics at uni, you explain these things better than most of my Professors. I feel like it fell into place now!
omg this statistics series is awesome! they really put effort in this.
I'm in college now and have been watching videos from this channel since high school. Needless to say, they've been so helpful. So crazy and great I can find a resource as great as this on RUclips!
PSYCH MAJORS, WHERE YOU AT!?
One 12min vid explained this topic better than six hours of classes.
"Reductio absurdum!!!" Yelled Harry Potter pointing his wand at Voldemort.
And just like that, the Dark Lord turned into a giraffe with 200 spots
well, the spells in harry potter are inspired by latin
taking 4000 level biostatistics and this is much more effective, and efficient, explanation of hypothesis testing! I feel like I wasted hours reading a book that is written in archaic jargon, when everything I needed to understand the logical concepts is right here.
Reductio ad Absurdum sounds like a magic trick!
Great timing, came in just as my class started going into p-values ^^
Please make a series on linguistics too. After all, language matters.
I'm very thankful for you breaking it down so well. I got worried with the last video. Love the series!
FINALLY understood p value! Thanks!
This was better than any explanation I have read so far
Heart melted by giraffe wave!
statistically significant
10:27
Statistically Significant = unlikely to be due to Random Chance alone
It's more like 10:12
you should add: given that the null is true
I'd love to see a crash course on psychometrics (CTT, IRT etc.) - to combine those psychology and statistic courses!
thanks this was extremely helpful
Wow!!! That was amazing, really clarified few things that were disturbing me. Thanks!
I love the giraffe example because I work at a zoo and I run the public giraffe feeds XD
Couldn't pay attention to the null hypothesis. Guy lounging on a tree and eating was way too distracting.
literally i couldn't follow the null hypothesis for those eating scenes either what the heck!! that was so distracting why did they do that!
@@deeghali8719 Exactly I was thinking I'm the weirdo, always about eating :P
My god, I think after watching this about 3 times, I've got it
8:13 - Where is 8.99% comming from? I've got about 6% with this R code: "1 - pnorm(2400, mean=2300, sd=(500/sqrt(60)))"
Yup, I got the same thing.. 8.99 is wrong.
Same thing: ~6%.
60 samples: (2400cal - 2300cal)/(500sd/sqrt(60)) = 1.549 z-score => 6.0691% complementary cumulative
6:10 golden words
What's coming will be the best part. It's very relevant in today's scientific enviroment,
I was promised golden pants! And you wonder why DFTBAQ doesn't take off... smh
Nyt Mare I WAS PROMISED DFTBAQ PANTS! LIES! ITS ALL LIES! THIS IS WHY THEY SHOULD HAVE STUCK WITH HANK AND JOHN
What does the Q stand for?
This series is significant.
Alternative way to define the p-value:
The probability of wrongly rejecting the null (hypothesis)
That is called a type 1 error.
I love this series!!!
I find it difficult to elevate my competence in statistics... maybe I am not simply predisposed to possess the proclivity of a Math Genius.
Awesome!
*_...sometimes statistics talks so slightly about usability, that it looks offtrack from any-use-at-all (mathematics isn't to blame)-When I consider votation outside the entropic zone of indistinguishability from random-voting, I include the likelihood of rejected results being returned for a specific reprocessing (e.g. contested Laws returned to the Supreme Court whose workload is fixed), and I perhaps-arbitrarily for otherwise-general use select σ√2π as where the 'Normal' bottoms-out..._*
we get assigned these videos for our stats class and I literally have no idea what ur talking about half the time lol
Reading for data science and machine learning
I'd like to see you explain why it would an reductio, that would be hardcore scientism if you'd ask me.
I'm in love with this lady ❤️ she's amazing!
THANK YOU!!
Ytterbium-171 atomic clocks demarcate a second with their transition frequency of 518, 295, 836, 591, 614 (518 trillion and change), with an Allan's deviation of 10^17! And you thought that you had control over your p.
How long have you waited to tell that joke? I love it.
Echoing the comments about food...Food serves as a such a perfect source of relevant and manipulatable examples for a stats course. Three thoughts:
1) She does a great job using food in just this way in every one of the videos I've watched so far (up through 21)
2) People with eating disorders should look to Khan Academy for their video-based stats ejumukashun. Though inferior to CC in myriad ways and overall, at least his chicken scratch drawings and overly assumptive examples in no way resemble something comestible. His videos rival unadorned chicken breast in blandness and enjoyability. CC videos, well, chicken parm baked by a Neapolitano grandma named Maria!
3) She's an obvious plant by the Koch brothers and big-ag.
good job
If you get a p-value that is in the 90s, it's guaranteed to be X-TREME!.
It’s a crime that the intro doesn’t use “DFTBAQ” in the speech bubble for the intro.
Could you please talk about effect size.
And if it’s as important as statistical significance. Especially with complete population stats (like census).
So we divided the us population into males and females, can we use effect size?
25 baby giraffes! 😍😍 Where is this zoo!?
+CrashCourse: In the title, I think you mean "hypotheses" (plural)... and the "p" and "v" should be in lower case.
4:54
Hey what softwares you use to make graphics and animations?
Would this not also mean that we should expect "statistically significant" findings to be incorrect up to 5% of the time?
No. You should expect statistically significant findings to be incorrect more than 5% of the time, because statistically insignificant findings are very rarely reported. Also keep in mind that you can sample your population 20 times, for which you can expect 1 significant finding. To counteract this, you correct for multiple testing by controlling the family wise error rate or false discovery rate.
Can we get a crash course economics, and have half of the series to macroeconomics, and the other half to microeconomics.
I lost them when people started eating.
Was that guy eating a clove of garlic?¿
I used program to generate a normal curve stated in last problem with mean of 2300 and SD of 500/sqrt(60) to get p value of 12% and not 18% as said in the video. CC please expaln?
Notice how she says Buzzfeed 6:10
Why doesn't this series have a playlist? I want to share this. This series needs a playlist. Please fix.
Nevermind, the dumb RUclips app doesn't list more than 20 or so playlists....which is dumb.
Yeah... I said it... I said dumb twice... Dumb! ;-)
It's good to know, that as a YT user, you can create your own playlists, and share with your friends.
I love baby giraffe
Why couldn't you have had these when I was in High School? haha
hungry while watching...and then 03:50 happens................
Where was this six months ago?!
Wait, how are p-values determined in the very first place?
Free Again After the data is collected, any of the suitable statistical tests (e.g., t-test) can be performed to get the p-value.
Jyoti Yadav thanks! I don't think she mentioned the t-test in this video (or I wasn't paying attention) but I'll give it a look.
Free Again No, she didn't mention the it. I am just telling you what I know from my biostatistics class. 😅
You take a look at the distribution of your null hypothesis and calculate the area under the line from the value of your test statistic towards infinitely more extreme. The area under the the line of the entirety of your null hypothesis distribution should add up to exactly 1, thus the area that you are calculating for your statistic has to be smaller than 1.
arbitrarily.
BOy this suRe Is iNterestinG. ;)
Nerds who love nerds who love giraffes who love giraffes!
Im a little disapointed that there were no gold pants
Gold pants?
So reduction ad absurdum is not always a logical fallacy?
Can someone explain to me this conclusion 8:08 ? : I understand that 9% of mean caloric intake are higher than 2400. And that since the distribution is symmetric, 9% higher than 2300 is 9% lower than 2300. But how does they add up ? WHY THE HECK do we care to use the symmetric rule to say that 18% are away from 2300. Where does 2400 fit in this conclusion ??? I need help seriously y_y
The p-value is the probability of the data randomly occurring. If the p-value is high, then the data is considered not significant and you fail to reject the null hypothesis. If the p-value is low, then the data is likely not random and you have statistically significant data (you fail to reject). The p-value for this problem is .09, while the standardized p-value cut off in statistics is .05. In this example, the probability of the data randomly occurring is 9%, so we can't say the data is significant since the probability greater than 5%.
@@freezerburnfreeze Thank for you answer although that is not what I wanted to understand, I actually do understand well the p-value but I don't get how a two sided p-value work in this example. They use the symmetric rule but it is not the logic behind it that I don't understand, it is how do they manage to use it here that is not clear.
In this case, the question is whether people with gene X eat a different amount of calories than the general population (NOT whether people with gene X eat HIGHER amount of calories). Although we got the information that the mean of a sample of 60 people with gene X is 2400 and is greater than the mean of general population which is 2300, the mean of the all the people with gene X might be smaller or greater than 2300, so we need two cutoff numbers on both sides to decide whether to reject NHST and it's .025 for each side, and comparing .09 to .025 is just same as comparing .18 to .05.
I just had an exam on statistics today....
I miss John green
Where was this video 2months ago
i don’t get it.
Why food examples? I am hungry now.hehe
Why the hell did the guy at 4.00 straight up bite into an onion????????????
Ok but where are the gold lamé pants?
Not 1st
I'd really like to love this series, like the many excellent other subjects, but it doesn't quite have the same flair.
Disappointing to see logical contradiction compared to unlikely.
gold lame pants????
Gene X? Lets call it something different so that Chromosomes 22 and 23 are not confused with it.
where are the pants
Delivery was much too fast and the graphics were not on the screen for long enough.
You can change the speed of the video, if that helps?
Slow down the video and stop your entitled complaining over something provided for free, boomer.
yayy 1st?
You say that the current consensus is that alpha should be 0.05 - this is standard in the social sciences. But ask a physicist? When they found the Higgs boson they went out 5 standard deviations from the null hypothesis mean.
what
I took my statistics test on tuesday, wasn't really proud of what I wrote ...
TK H make peace with the outcome.
.
She isn't wearing her gold lame pants!
I hate to nit-pick, but your examples misused standard deviation. 175 spots with a standard deviation would have a bell curve MUCH wider than what is shown. The bell curve shown has a mean of 175 with a standard deviation of approx 11 or 12. Please make your graphics match your examples.
the graphs in this example use the standard error, not the standard deviation since it's the mean number of spots for a group of giraffes not just one!
anyone else super grossed out by the men eating
First
She could not have been more unclear in her definitions and examples. She literally made it as complex and confusing as possible even though this concept is actually not so.
I find Khan academy hypothesis topic much simpler than crash course , isn't crash course ment to be more simple to understand
There are other factor than simplicity to consider. For example, I find the speaker on Khan academy very hard to listen too.
REEEEEEEEEEE
Riddle me this lady, what is the probability of me losing my virginity before im 40?
shout me out first comment
There are so many things wrong in this video I can’t even start to describe. Just get a statistician to take the show and correct the misconceptions, please.
Bernardo Powaga Nothing jumped out at me. Could you name one or two misconceptions in the video? Not a statistician, but interested.
I didn't notice anything wrong. Please give an example
Stating that chance alone cause a test to be wrongly significant and use of hard cutoffs are the most common and dangerous misconceptions here. Just read the ASA statement about p-values (February 2016 if I remember correctly) which talk about these issues.
Bernardo Powaga about the cutoffs, she said that there's a lot of discussion on if it's good to do that and she'll dive further into that next video
@@BernardoPowaga There is a whole episode in the serie about that p-value "standard" discussion and the reproductibility crisis in sciencitfic research, tho. And she does mention the ASA statement and provide a link to it.