for real though, videos like these are so helpful along with the textbook sometimes even. When professors are explaining it I feel they're going off the top of the head so sometimes its explain oddly and confuses me even further.
This video just made an entire semester of statistics make more sense. Thank you, this information will help out a lot for the final. Much Appreciated!!
What an amazing explanation! I banged my head reading quite a lot, still didn't get it, and watching this video I will remember it forever now! Really great job James! Looking forward to watch more such videos!
I’m on Level 2 of the CFA designation and this blew my mind. Thank you for the clarity and simplicity. I feel like I’m walking away with a better understanding of
I can't believe how simple this was! the brilliance is always in the basics! I've been trying to understand why instead of "thats just how it is" and neither my teacher or my textbook have made sense to me as to why! Thank you so much you made everything click after the coin example!
this is just so great i must appreciate your effor and the simplicity woth which you explained the concept,Thank You so much please continue to make such contributions
this is the most intuitive on df, the fact in reality that we never knew value of true population mean, and sd always come after, in most cases n-1 is the reality of our data because as soon as we come up with an estimate of an average' the last piece of information is no longer needed. because that last piece of datapoint violates randomness of data so it has to be tossed out
This video is of virtue! Degree of reedom is a very hard concept to understand and other internet searches do not help much. I cannot thank you enough for this exceptional explanation.
I completely understood your explanation. Having calculated the mean of the sample, the DOF reduces by one, as the nth value gets fixed. But, why can't I make the same argument for the whole population? Shouldn't DOF for its variance also reduce by one, since we already have the mean calculated? So, by that effect population variance shouod also be divided by N-1 ?
Plz is there an answer to this? Same question here!
4 месяца назад
There is a crucial difference between the population mean and the sample mean; only the latter is an estimate, and it is an estimate of the former. The consequence of this fact is that you lose one degree of freedom when you calculate the mean from the sample data, and that's why we divide by n-1 when the mean we are using is only an estimate, and that's also why we divide by n when the mean we are using is a fixed value calculated by a set of fixed data.
I don't know if you'll ever see this but I have a question that relates to the calculation of sample variance versus population variance, where for population variance calculation, you don't need the n-1 degrees of freedom. Given that you know the mean for the population as well as for the sample and so effectively an n-1 dof, which only 'n-1' not used for the calculation of population variance. And by the way, your explanation of degrees of freedom is absolutely brilliant. Thank you so much for this video
Thanks for a very clear explanation. I have a question, though. In the example about standard deviation of a sample, since we knew in advance the mean Xbar, then we need to divided by (n-1) since this is the df of this. However, in the formula for sd of a population (assumed that we knew the mean muy) , it is divided by N. Why is this the case? Why can't we use (N-1) as with the sample? Don't we know muy in advance?
I still don't get why the n-th value doesn't contribute to the standard deviation. How can we say that only n-1 pieces of information contribute to it when in the numerator, we calculate the square of the deviation from the mean for all n values? I understand that (x1-xbar) + ... + (xn - xbar) = 0, so if we know what (x1-xbar)^2 + ... + (xn-1 - xbar)^2 is, we can work out (xn-xbar). What I don't understand is why it matters. I mean, we HAVE all n values, we don't have to work anything out. And we use all n values in the formula, so why act as if we didn't?
@@alijulaeerad5258 Could you give an example of that? Are you talking about not knowing all the scores of the population, and estimating the population standard deviation from the sample standard deviation? If so, the sample scores must still all be known right? Or are you talking about not knowing all the scores in a sample? Then what standard deviation are you estimating? Also practically why do statisticians estimate standard deviation?
@@Han-ve8uh we try to estimate the standard deviation of the population because we do not have all the scores In the population we only have all the scores in the sample. So in order to estimate the standard deviation of the population we assume that we know all the scores but one because that one score doesn't contribute to the standard deviation.
I understood from the degrees of freedom perspective but I still do not understand why the Nth value do not make any contribution to the value of Standard deviation/Variance
Please what is the degree of freedom when runing mann Whitney test to see difference between to groups ,and for maki g spearman correlation involving two groups
Thanks for clearly explaining. My conclusion about df: Within a formula if you know already other parameters (not include values of samples), how many minimum values of samples do you need to know for imputing all values of entire samples.
How exactly does this apply in the subject of motion? In helicopter flight for example, there are typically two main things that determine how the helicopter may move; the main large propeller and the small propeller that is stationed at the end of the tail. In this scenario, since there are two main contributors to how a helicopter may move disregarding outside influence such as air resistance what would the degree of freedom be or how would you predict it since the you can perform several different types of movements along several axis solely through the two inputs I stated earlier. Thank you very much.
The way I've been crying over this for 3 weeks and this guy got me to understand it in a 10 minute video
for real though, videos like these are so helpful along with the textbook sometimes even. When professors are explaining it I feel they're going off the top of the head so sometimes its explain oddly and confuses me even further.
This video is fantastic and much needed on the internet. Please carry on making content like this. Thank you so much!
This video just made an entire semester of statistics make more sense. Thank you, this information will help out a lot for the final. Much Appreciated!!
After watching this video, there is a portion of my brain which is unlocked.
An outstanding video James. Bring more videos like this.
RUclipsrs like you makes RUclips such a great place! thanks a lot for nice interpretation!
This was the best explanation of degree of freedom I have ever seen on RUclips or any other reading material., thanks Mr James.🙏
Nothing can beat this way of explaining degrees of freedom. Thank you sir
What an amazing explanation! I banged my head reading quite a lot, still didn't get it, and watching this video I will remember it forever now! Really great job James! Looking forward to watch more such videos!
OMG! This is the best explanation I've ever heard! Thank you, Mr. Gilbert!
I’m on Level 2 of the CFA designation and this blew my mind. Thank you for the clarity and simplicity. I feel like I’m walking away with a better understanding of
Same for me. Surprised its not really explained anywhere.
AMAZINGLY clear & well-done. You are the best!!!!! Thank you, thank you, thank youuuuuu.
Make so much sense now, I'm really thankful for this video of yours. Thankyou so so much Mr. Gilbert.
Best video thus far to explain the concept of "Degrees of Freedom (DoF)" 👍
Incredible content. I can always count on some youtuber to explain something better than the academic course that got me here.
Certainly the best explanation of df I have come across. Thanks for your effort and ingenuity.
you don't understand how happy i am to have come across this video
I can't believe how simple this was! the brilliance is always in the basics! I've been trying to understand why instead of "thats just how it is" and neither my teacher or my textbook have made sense to me as to why! Thank you so much you made everything click after the coin example!
man you should make video a lot about statistics,the way how you explain the thing is really simple and good
your voice tho!! increases the probability of easier and faster understanding for pretty much any concepts.
The best explanation on degree of freedom so far , I really appreciate your knowledge on stat.
this info literally made me one step further in life! now I can pass the dynamic lab defend.
this is just so great i must appreciate your effor and the simplicity woth which you explained the concept,Thank You so much please continue to make such contributions
Excellent explanation... It got too clear for me now. Thanks.
Thank you for posting this! Clarifies so much!
After watching 7 videos on degree of freedom...finally got the perfect video....I cant thnx enough man....God bless u
Incredibly intuitive!! Thank you, sir, for such a lucid illustration.
the only video on youtube that cleared the topic for me! thank you!
the best explanation of degree of freedom, really appreciate
this is the most intuitive on df, the fact in reality that we never knew value of true population mean, and sd always come after, in most cases n-1 is the reality of our data because as soon as we come up with an estimate of an average' the last piece of information is no longer needed. because that last piece of datapoint violates randomness of data so it has to be tossed out
I loved it, thank you so much! Really impressive how you put it so simple
Absolutely BRILLIANT! Thank you!
I read the comment first, then watched the video - I was not disappointed. This guy is good.
W
Amazing Video for conceptual understanding
Man you're just a savior.❤
This video is of virtue! Degree of reedom is a very hard concept to understand and other internet searches do not help much. I cannot thank you enough for this exceptional explanation.
Dude you did a fantastic job . I tried every where but I was not getting the concept . You did it in one go. Really thanks. Apppreciate it.
I watched a few videos and only yours helped me understand the concept. I like graphics!
Best explanation on DF ever! Thank you so much.
Very clear explanation of DF, Thanks, James ! :)
Thank you. 20 years after leaving college with a B- in statistics, I finally got an idea what "df" is. Thank you.
This is the best video for Degrees of freedom.
Nicely explained, simple but effective examples
The best of the best explanation of DF. Thanks!
Best vedio on youtube on this topic. Thanks a lot.
Beautifully explained! Now it makes 100% sense why Variance and Standard is divided by N-1 instead of N.
this video should have 119 BILLION views, literally, thank youuuu
I paid thousands of dollars for my tuition and ended up searching video tutorials here...I hope every professor can make things clear in this way
I completely understood your explanation. Having calculated the mean of the sample, the DOF reduces by one, as the nth value gets fixed.
But, why can't I make the same argument for the whole population? Shouldn't DOF for its variance also reduce by one, since we already have the mean calculated? So, by that effect population variance shouod also be divided by N-1 ?
Plz is there an answer to this? Same question here!
There is a crucial difference between the population mean and the sample mean; only the latter is an estimate, and it is an estimate of the former. The consequence of this fact is that you lose one degree of freedom when you calculate the mean from the sample data, and that's why we divide by n-1 when the mean we are using is only an estimate, and that's also why we divide by n when the mean we are using is a fixed value calculated by a set of fixed data.
extremely well-explained! Thank you James.
That was beautiful.
just simply wonderful explanation
excellent illustration and explanation of the topic, kudos
Thank u so much!!!! STAY BLESSED!!!!
Fantastic your video! It is the explanation I exactly looked for to show my students
This is very helpful. I teach an introductory stats class and this will help me explain df to my class.
3 hours of complicated over explained knowledge, condensed down into a 10 minute video. Thank you!
I don't know if you'll ever see this but I have a question that relates to the calculation of sample variance versus population variance, where for population variance calculation, you don't need the n-1 degrees of freedom. Given that you know the mean for the population as well as for the sample and so effectively an n-1 dof, which only 'n-1' not used for the calculation of population variance.
And by the way, your explanation of degrees of freedom is absolutely brilliant. Thank you so much for this video
Thank you!!!! I was SO confused by my textbook and I finally get it!
I love your explanation and the examples you gave. Thank you for your help 😊
By far the best explanation in You tube
Simplicity at it's best, I wish I had known this video when I was still at college 🙏
Its really great and easy to understand.
Tremendous video; the best video
Thank you! This was very helpful and straight to the point :)
Thanks for a very clear explanation. I have a question, though. In the example about standard deviation of a sample, since we knew in advance the mean Xbar, then we need to divided by (n-1) since this is the df of this. However, in the formula for sd of a population (assumed that we knew the mean muy) , it is divided by N. Why is this the case? Why can't we use (N-1) as with the sample? Don't we know muy in advance?
Great video! Thank you
Absolutely efficiently and clearly explained! Thank you!
Your videos are very helpful! Thanks a lot!
It's really sad that you didn't continue make more videos though =[
This is one of the best explanation👋
This video made me understand this concept well. Thank you!
This really helped me have a better grasp, thank you!
very good..thanks James!
the best and easiest explanation ever
The best explanation on youtube.
Thank you for this video.
Wow! Great content. Thank you.
Best description I've seen so far.
Excellent content.
Great video 😊
beautiful explanation man. Thanks!
Amazing...
best explanation so far,
This is amazing!
Thank you for the easy explanation!!!
I still don't get why the n-th value doesn't contribute to the standard deviation. How can we say that only n-1 pieces of information contribute to it when in the numerator, we calculate the square of the deviation from the mean for all n values? I understand that
(x1-xbar) + ... + (xn - xbar) = 0,
so if we know what
(x1-xbar)^2 + ... + (xn-1 - xbar)^2
is, we can work out (xn-xbar). What I don't understand is why it matters. I mean, we HAVE all n values, we don't have to work anything out. And we use all n values in the formula, so why act as if we didn't?
sometimes in statistical tests we actually don't know all the scores and we need to "estimate" the standard deviation.
@@alijulaeerad5258 Could you give an example of that? Are you talking about not knowing all the scores of the population, and estimating the population standard deviation from the sample standard deviation? If so, the sample scores must still all be known right? Or are you talking about not knowing all the scores in a sample? Then what standard deviation are you estimating? Also practically why do statisticians estimate standard deviation?
@@Han-ve8uh we try to estimate the standard deviation of the population because we do not have all the scores In the population we only have all the scores in the sample. So in order to estimate the standard deviation of the population we assume that we know all the scores but one because that one score doesn't contribute to the standard deviation.
Excellent explanation. Thank you
Best explanation
I understood from the degrees of freedom perspective but I still do not understand why the Nth value do not make any contribution to the value of Standard deviation/Variance
super Excellent video
Please what is the degree of freedom when runing mann Whitney test to see difference between to groups ,and for maki g spearman correlation involving two groups
Excellent!!
Great video.
This video is world-class. The likes to dislike ratio says it all!
Thank you for this great explanation.
Thanks for clearly explaining. My conclusion about df: Within a formula if you know already other parameters (not include values of samples), how many minimum values of samples do you need to know for imputing all values of entire samples.
Thank you for this video. That was a great explanation!
How exactly does this apply in the subject of motion? In helicopter flight for example, there are typically two main things that determine how the helicopter may move; the main large propeller and the small propeller that is stationed at the end of the tail. In this scenario, since there are two main contributors to how a helicopter may move disregarding outside influence such as air resistance what would the degree of freedom be or how would you predict it since the you can perform several different types of movements along several axis solely through the two inputs I stated earlier.
Thank you very much.
Good video. Thank you!
Very well done, thank you!
Fantastic explanation!