Pearson's chi square test (goodness of fit) | Probability and Statistics | Khan Academy
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- Опубликовано: 9 ноя 2010
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Pearson's Chi Square Test (Goodness of Fit)
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you make me want to burn my statistics book. I just spent 2.5 hours trying to understand a chapter and came out clueless, and then you made everything perfectly clear in 15 minutes (i paused a few times)
YOU ARE AMAZING
thank you so so so much for making this. you don't understand how much this helped me; my textbook could not have done a poorer job explaining it
most statistic books should be burned anyway
also statistic teachers
He is really amazing
The ASA Statement on p-Values: Context, Process, and Purpose
www.tandfonline.com/doi/full/10.1080/00031305.2016.1154108
"Failing Grade: 89% of Introduction-to-Psychology Textbooks That Define or Explain Statistical Significance Do So Incorrectly"
journals.sagepub.com/doi/10.1177/2515245919858072
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Hi there, thank you Khan Academy this really helped me and its already 5 years since this was uploaded. I am so glad to be born into this generation of freedom of information online.
It's 6 years since you made this comment.
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But my dad didn't let me have access
literally the only video on youtube that gets right on the point! No bullshit intro, just right to point on what i need to know, Love it!
I have massive respect for your work, man! Thanks for making people throughout the world more educated, that´s one of the essential things this world needs. And it´s one of the essential things I need haha.
you are the reason im getting a degree at harvard
Did u get that degree bro it's been 7 years can I get a update?
hes also the reason your degree is overpriced
I wonder if you had to also watch his videos to study for stat tests at Harvard ;)
@@bakhodiryakubov3981 I'm doing a Master in Physics at Oxford and I've found these videos more useful then my statistics lectures lol
@@randomman1000tweeny1 wow didnt expect that
it's relieving to read others in higher levels of school similarly benefiting from these vids. They're a lifesaver. Thanks Sal!
This material helped me out a lot! I know about khan academy since about 5 years ago and i just want to tell you guys to keep doing what you are doing, you probably account for more than 40% of my education
A clarification for anyone arriving directly at this video like me: the definition of the chi squared statistic for a sample is the sum of (x-E(x))^2/s^2, where s^2 is the variance of the data. When the variable is Poisson-distributed, like in this case, then you are in the particular case where s^2=E(x), as appears in the video
helpful, thank you!
Thank you!! This example helped me a lot in understanding other purposes of Goodness-of-fit test. Really appreciate it!!
When the AP test is in 2 hours and you're finally trying to study 😬
Statistics is fucking impossible to study for. I've never taken such a dry class in my life
i study the time im taking the test
Why do you think it is boring? personally I quite enjoy it.
I’m actually cramming for a university exam in like 4hrs...
@@stoirmdraodih6810 same right now
At last! Math & statistics feel approachable due to you. Thank you, Khan Academy!!!
Great explanation and sample. Just what I was looking for. Thanks.
so the p-value would be 0.043293 which is < 0.05 so reject the null hypothesis - same result as using critical values 11.07 < 11.44.
Wow you explained this so well, I actually got it! Thank you :)
Thanks for the video, this just explains how to, but is there a video on why the difference between observed and expected follows Chi-squared test? And also does the expected distri (e.g. normal vs binomal vs possion) matter? what is the proof for that?
Perhaps the best chi2 explanation that I have come across. Thanks
Thank you so much! You just taught me how to calculate Chi-squared and my finals are tomorrow. :)
how was the exam? 4 years :D
How was the exam 8 years ago?
@@thewilmarvelfan 12 years?
thank you soo much for uploading....amazing explanation...so much clarity
What a classic video!!!!.... Understood almost everything in 15 mins
Wow, that was a very nice example and intro to chi-square! Great job, Sir Khan!
Man, Sal, i thought i was done with khanacademy in grade 12 and here i am in my final semester of engineering :')
Awesome. Thank you.
hopefully the complete problem will be stated.. thank you
Thanks a bunch. It helped me with the homework.
well explained and clear and easy to understand. thank you xx
The Chi-Square distribution is a sum of squares of standard normal variables Zi. What this test is doing is assuming that the squared errors between the observed and expected distributions are distributed ~ Chi-Square. Makes it a bit easier to understand the test when you understand the motivation behind using the Chi-Square distribution.
Its Funny how I pay my professors/school thousands of dollars per semester and yet Khan always teaches me better for free.
Pay khan sir as well than if you feel like this
This is so beautifully done, many thanks.
Thankyou very much for this, the explanation is so clear and so good.
Thank you - this was so helpful!
thank you so much :)
question; do they always give you the percentage for the expected? because in all that i have done i had to either multiply the row total by the column total divided by the grand total or either dividing the total amount of scores by the amount of levels (the no. of days in this case) was i doing it wrong?
I'm still a bit confused about the conclusion.
The calculated value is higher than the critical value.
The smaller the P-value, the more significant the result.
The smaller the P-value, the higher the cricital value.
Thus I'd assume the hypothesis should be accepted, rather than rejected.
Otherwise I'd use a P-Value of 0.01 rather than 0.05 and the calculated value would be lower than the critical value and thus be accepted which makes no sense to me.
Realize the following fact. The more the observed data deviates from the expected data, the higher the differences between those values and so a higher Chi-squared value.
Yes you would accept the null hypothesis if you had used a P-Value of 0.01. Lower P-value means you need stronger evidence for you to change your default assumption / null hypothesis. There is a greater than 1% chance the owner is right given what you saw. In the video he rejects the owner's distribution because it has a less than 5% chance.
Fantastic video. I teach Stats & forgot how to do this. Great refresher
1st year AP Stat teacher loves Khan videos... Thank you Sal :)
1:53 What is trying to be said with"a result more extreme than this". Is it a distribution that fits the Owners Distribution less ?
Well explained, thank you!
This cleared a few points up. Good video from Khan.
*subscribes as a thank you for cutting some of the unending stress I am exuding from my stats final in 5 hours* *nervous smile*
Thanks for this test. Made it much clearer.
Very nice, thank you for explaining this
Thank you soooooooo much. You are the best teacher EVER!!!
Thank you very much.....excellent explanation
This was so helpful! Thank you Khan Academy and you guy who made this!
David Hager The guy who made the video is Khan, it's one guy that made evrything basically.
This video was suggested by my bio professor & he was 101% right. This video makes it super easy :) thanks
is there another video like this where it shows the formulas for each step? thanks
Thank you so much for your great lecture videos! I have one question if I may. I followed from Chi Square Distribution video 1 to here. And just confused that is that (30-20)^2/ 20 an x^2 in your Chi Square distribution definition? Basically, is x = (one_observe - mean ) / sqrt(mean) a standard normal distribution? shouldn't it be (one_sbserve - mean) / standard_deviation a standard normal?
THANK YOU :* video is comprehensible :)
So you would use this Chi Square goodness of fit test to determine whether a set of data came from a particular distribution?
awesome! Thanks so much!
Thank youuuu it really helped 👍🏻💙
It is very unfair to dislike this tutorial.
Thank you, amazing explanation
Woah! I see and I understand! Thank you!
graduate level student is learning from Khan videos... Awesome. thank you Khan academy.
man this is a gem....
ik its been a decade but thank you so much, hypothesis tests in general confuse me a lot
Over 7 years and this is still very useful :)
12 years now
and its still helpful
thank you very much!
Very explicit. Thank you.
Is anyone equiped to explain the history or logical background behind df = 5 and if we had 5 sums, we would be able to find out the 6th sum? Does it have something to do with fitting the summed values to the Chi squared curve and somehow knowing the 6th point from that?
I remember when learning about this test that if the normalized value for one of the columns is less than a particular value, that you are supposed to group it with the next column until your combined normalized value is greater or equal to the specified value. If I'm not mistaken that number is 0.05. Am I correct? For example, if (Observed-Expected)/Expected = 0.02 for one column and the column to the right is 0.34. Then you would add 0.02 + 0.34 to get 0.36 and you'd lose a degree of freedom.
Can you please elaborate what 'extreme' means? It's used a lot in this video. Thanks!
thank you .. that really helped me :)
13 years ago , still holds its title for the best explanation ❤❤
Thank you!!
REALLY WELL EXPLAINED KHAN ACADEMY - WELL DONE
great explanation!
Thank god for you khan academy.
Thank you got an exam in 2hrs
What is the t value u enter when creating a table. And the a= . Is a=.05. So a chi sqaure test was conducted for goodness of fit (a=??)
Thank you. Thank you. Thank you!
Thank you for that Sir.
really great, thanks
After rejecting the null hypothesis, how might one go about investigating the "true" or better expected percentages?
Sal, another clear video. However, may be you could have talked a little bit as to why chi-sq is appropriate for this particular type of problem (or similar type) - how would a student know when to select the same distribution for a problem at hand.
Thanks for this video...I read the 1st couple of page in my Elementary Statistics book and was sooooooooo confused. You made this so clear! The only thing was your df (degrees of freedom)...I thought this was supposed to be number of columns minus one x number of rows minus one.
Thank you!
Saved. My. Life.
Dude, you a genius!!
many thanks once again
It's quite funny how every time you say "statistic" you have to slow down and make an effort to get it right. But seriously, I've watched most of your videos from the stats playlist and it's been a great deal of help. Thanks Sal!
This will go down as one of the most clutch explanations of all time
Well explained,,,,thank you sir
why does the X² test divides to the expected value and not the variance?
Thanks for this!! My exams are in 3 days time.
dude, just ..... thank you !!!
Thank you so much
thank you so much, you're a god among men
AP Stat Test Tomorrow, life-saver!
it's funny how you always repeat yourself but that makes your video's so easy to understand! thanks for your help!
THANK YOU
thank you so much
Hi, ..can you please suggest a test to see if there is a difference between 2 groups of female mice (treated and untreated) with respect to the number of male and female pups delivered.
Thank You :D
what is the explanation of when the number of sample goes up with same probability and pattern, the resulting hypothesis changes from accepting H0 to rejecting H0?
Hey can you do some videos on error propagation to go with your statistics videos?
thanks
As null hypothesis means that attributes are not related so how owners distribution is correct? Please explain I'm confused about that statement
One thing I don't entirely understand is why do we almost always choose a significance level of 5%? And what exactly would we gain or lose if we make it more or less than 5%? If we make it higher than 5%, doesn't it then make the hypothesis more difficult to accept, since it would require more accuracy to accept it? This would seem to make it more easy to reject a true hypothesis, but at the same time, doesn't it also make it more likely that we won't accept a false hypothesis?
Edit: I read that medical experiments have a tendency to choose a significance level of 1%, but wouldn't it be safer to choose a higher significance level, so that a false hypothesis won't be accepted, or did I misunderstand something?
The choice of a significance level will be appropriate, not only to the industry but the precision of available techniques. If your measuring/quantification techniques have an accuracy of micrometres choosing a significance that equates to an accuracy of nanometres is not only inappropriate but impractical.
Thank U!!
thank you