If you like, please find our e-Book here: datatab.net/statistics-book 😎
@gopikrishnap4225 Жыл бұрын
You have not only explained the Standard Deviation calculation in an easier manner with an example but also answered the common questions about Arithmetic mean and Quadratic mean. Thank you for the great video.
@Grace-bz3px6 ай бұрын
This is by far the simplest and clearest explanation I found thank you!
@datatab6 ай бұрын
Glad it was helpful! Regards, Hannah
@margaritap.11217 ай бұрын
Thanks a lot for explaining it so clearly and slowly. Most videos go too fast and I have to pause all the time, but with you it was perfect!
@datatab7 ай бұрын
Glad it helped and thanks for your nice feedback! Regards Hannah
@KB-tt4zt8 ай бұрын
Variance and standard deviation are both measures of how spread out a set of data points are, but they differ in how they express this spread. Variance is like the average of how far each data point is from the mean (the average). It tells you how much the data points vary or spread out from the average. If the variance is large, it means the data points are spread out widely from the average. If it's small, the data points are closer to the average. Standard deviation is simply the square root of the variance. It's essentially a measure of how much the data points deviate from the mean. So, if the standard deviation is large, it means there's a lot of variability among the data points. If it's small, the data points are more clustered around the mean. Think of it like this: variance gives you a measure of spread, but in the same units as the data (for example, if you're measuring length, the variance would be in square units). Standard deviation is more interpretable because it's in the same units as the original data, making it easier to understand how spread out the data is.
@t_4_traveler147 Жыл бұрын
U r the best i finally found someone who can explain this clearly with examples
@2006akk7 ай бұрын
very clear explanation with visual and speak slowly so we can catch every steps, thanks subscribed!!!
@datatab7 ай бұрын
Glad it was helpful and many thanks for your feedback! Regards Hannah
@GAUTAMKUMAR-wc4ht Жыл бұрын
One of the best videos on SD & Variance, thanks a ton for keeping things simple.
@EsauRamirez-Perez-v9x Жыл бұрын
Literally was lost, mainly because my professor goes fast and I cant catch up with what he says but holy am I grateful for this video. I understand most but this just help clarified what I am learning by a significant amount!!
@malwalsabino519 Жыл бұрын
The best explanation of standard deviation ever. For the first time, I have a full understanding of SD. Thank you so much
@Isaac-q9o3f8 ай бұрын
Thank you so much for explaining these terms as simple as possible.
@shutup421116 күн бұрын
Very informative. Thanks!
@archerdevАй бұрын
Great Lecture, thank you so much. Math bless you.
@hanswurst-gp7pi Жыл бұрын
Vielen Dank für eure tollen Videos! Ihr erklärt das Thema Statistik sehr verständlich und auf eine angenehme Weise. Könntet ihr (ähnlich wie zur Standardabweichung) auch ein Video zum Standardfehler des Mittelwertes machen?
@datatab Жыл бұрын
Hier auch vielen Dank nochmal : )
@AmanPatel-jl6eq Жыл бұрын
great explantion 👏🏻
@datatab Жыл бұрын
Glad it was helpful!
@Causer15678 Жыл бұрын
Thank you very nicely explained.
@SankalpJulme11 ай бұрын
this helped a lot. thank for the explaination
@datatab11 ай бұрын
You are welcome!
@eva42sh5 ай бұрын
this one is more clear explanation
@jwennermark Жыл бұрын
Just love it, thanks!
@datatab Жыл бұрын
Many thanks : )
@SIVAJI_333 Жыл бұрын
Well explained🤝🏻
@datatab Жыл бұрын
Glad you liked it
@gauravkinhikar8482 Жыл бұрын
Very well explained ❤
@danielmagantopizarro22627 ай бұрын
Gracias Hannah!
@datatab7 ай бұрын
You are welcome Daniel : )
@shikshabunjhoo7 ай бұрын
Thank you so much!!! This was so helpful :)
@datatab7 ай бұрын
You're so welcome!
@AngelsrelaxTuber6 ай бұрын
Good explanation
@datatab6 ай бұрын
Thanks and welcome, Regerds Hannah
@2460z_htdja9 ай бұрын
i really have to thank you for this explanation :)
@taashin2863 Жыл бұрын
I understood everything except one point Why in calculating the standard deviation of a sample we divide the mean be n minus one I mean this make it more accurate to represent the population ? why not just divide it by n alone ? Why exactly minus one ? Not minus 2 or plus one for example?
@niamatnaz Жыл бұрын
excellent explanation
@belalalaa4193 Жыл бұрын
Amazing video thank you for sharing this information.
@farhaatalhatash87939 ай бұрын
That is amazing! Thanks
@mehdismaeili3743 Жыл бұрын
Excellent.
@datatab Жыл бұрын
Many thanks : )
@Doparmiin Жыл бұрын
Die Stimme ist unangenehm anzuhören. Der Inhalt ist wirklich nützlich. Gerne mehr :) Gerne bei zukünftigen Videos nicht so überheftig betonen und auch die Sprachmodulation etwas reduzieren. So hatte ich das Gefühl, dass die Stimme glaubt, dass ich ein Vollidiot bin, der die Sprache nicht spricht.
@datatab Жыл бұрын
Hi vielen danke für dein Feedback! Das Mikrofon war diesmal leider ein wenig Laut eingestellt, daher ist es teils ein wenig hoch/kwitchig. Der Rest ist denke ich Geschmackssache und da es aktuell recht gut ankommt werden wir den weg erstmal so weiter gehen. Wie man hört : ) sind wir keine ausgebildeten Sprecher und keine natives, aber das muss bei einem KZbin-Kanal ja auch nicht sein : ) Das gleiche Video gibt es auch nochmal auf deutsch auf unserem deutschen Kanal: kzbin.info/www/bejne/l4OUlItvlsedl8k LG Mathias
@tjar13 Жыл бұрын
The voice helps me a lot actually. And the fact that you speak slowly also. So thank you. 🙏🏻
@jimnahmwangi4318Ай бұрын
so clear
@Amazingarjun9 ай бұрын
by adding 10 of each, var and std will remain same?
@Your_Dream_Journey Жыл бұрын
Excellent
@ThomasHaberkorn Жыл бұрын
is there a relationship (or a rule of thumb) of how big the sample size "n" should be at minimum to be confident that it wont change the standard deviation much for bigger sample sizes?
@farishanadiah5451 Жыл бұрын
Is datatab free to use?
@aminahassen7448 Жыл бұрын
Can't u just try
@marharytabohdanova9448 Жыл бұрын
thank you!
@MidnightSkylineMA24 күн бұрын
Phenom
@r.ganeshm7336 Жыл бұрын
😊nice
@fatehiabdo17406 ай бұрын
niec explaine
@datatab6 ай бұрын
Thanks : )
@otheanh530619 күн бұрын
oh my god, that's all i need
@bahaamahmoud5406 ай бұрын
divided by n or n-1??
@datatab6 ай бұрын
It depends on the situation!
@mosesbanda86717 ай бұрын
Powerful
@Simplifieddeeplearning3 ай бұрын
hello i am a bit confused after summing it up and divide by 6 i got 132 will you got 11.5 at 2:33 in the video please any one can help
@HidwisАй бұрын
The last step is that you need to calculate the square root of 132 which will get you to 11.5
@baitong13506 ай бұрын
Why n -1 tho? (Why it has to be -1?)
@datatab6 ай бұрын
Hi, this is a bit complicated but I will try. When calculating the standard deviation for a sample, it is divided by (n - 1) instead of (n) to correct for bias and get a better estimate of the population standard deviation. This adjustment is known as "Bessel's correction." Here's why it is done: 1. Population vs. Sample: - If you have a complete population, you would use (n) (where (n) is the total number of data points) to calculate the standard deviation. - In the case of a sample, which is a subset of the population, using (n) would typically underestimate the population standard deviation because the sample might not fully represent the population's variation. 2. Bessel's Correction: - By dividing by (n - 1), you adjust for this underestimation. The denominator (n - 1) provides a more accurate estimate by accounting for the "loss" of degrees of freedom due to the mean being derived from the sample itself. - In simpler terms, when you use a sample to estimate the population standard deviation, you effectively "lose" one data point's worth of information due to calculating the sample mean. Dividing by (n - 1) compensates for this. 3. Degrees of Freedom: - The use of (n - 1) is linked to the concept of degrees of freedom. When you estimate a parameter from the data (like the sample mean), you reduce the degrees of freedom because the sample values are constrained by this estimate. Dividing by (n - 1) corrects for this loss, providing a less biased estimate of variability. By using (n - 1) instead of (n), the calculated standard deviation from a sample more closely approximates the true standard deviation of the population, especially when the sample size is small. Regards Hannah
@adeebmahmood3 ай бұрын
@@datatab But why specifically n-1 and not possibly something even higher like n - 10, etc?
@ΣτελιοςΒουγιουκαλακηςАй бұрын
But why we use standard deviation instead of average deviation do not explained in this video
@dilnozaqoziyeva700011 ай бұрын
👍👍👍
@potawatomi1002 ай бұрын
Great programming and you do a fantastic job of explaining. Plus, I think you’re beautiful.
@yoliwis10 күн бұрын
“Persons” doesn’t exist, the correct word is people. 😊