Glad you like it! For similar videos with real-world examples you can check out our 365 Data Use Case series: ruclips.net/p/PLaFfQroTgZnzJn7VXKLuiZXPF1y5Wzflj
Leaving a comment just so you guys know I regularly watch your content and really very very greatly appreciate the effort you put in your videos. Thanks a lot
What is the y axis in the curve representing exactly and why the value of the mean is represented by a higher bar than the values bigger than the mean is it only me who found this explanation more confounding 🤔
Wouldn't the standard error of this distribution be sigma/sqrt(n) and not sigma as it says in the video? Sigma is the standard deviation of the population, not the standard deviation of the distribution of sample means.
I believe they meant the standard deviation of the sample mean distribution (aka standard error directly). They didn't explain on how you obtain that standard error which is exactly what you stated (σ/sqrt(n)).
And FYI, at 5:47 it should say should say "mean of sample means of 48" not "sample mean of 48"; and then maybe "standard deviation of sample means" for clarity.
IF the underlying population distribution is NOT NORMAL, and we have samples less than 30. Let's say the samples are size n = 5. I know the distribution of the sample means will not be normal according to the CLT. However, will the distribution have the same mean as the population mean, and will the variance be equal to the variance of the population divided by 5? Please let me know? thanks?
no and no, gotta either have a normally distributed population or n>30 for those conditions to apply (and it would be divided by the square root of the sample size, not the sample size itself)
@@VaiskHD Are you sure? I thought no matter how the population is distributed if you take large samples for a population the sample means will be normally distributed
This example was great. However, I don't think you need to increase the sample size to be more precise. Well indeed you will eventually reach the population size and there will be no need of sampling. CLT on the other hand talks about the number of samples. These two are not same.
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That was an excellent explanation. The fish tank example was really good to illustrate. Keep up the good work.
Interesting. please do more videos which can relate to real world applications.
Glad you like it! For similar videos with real-world examples you can check out our 365 Data Use Case series: ruclips.net/p/PLaFfQroTgZnzJn7VXKLuiZXPF1y5Wzflj
Leaving a comment just so you guys know I regularly watch your content and really very very greatly appreciate the effort you put in your videos.
Thanks a lot
Thank you, this means a lot! We are very happy that you enjoy our content!
Great example, thanks for simplifying CLT
Thanks a ton.!!!! This video made the concept clear.😊
this kind of example helps a lot
You are awesome, just wow. Thank you!!!
Great example! Thank you.
This question was asked in GTU Data Science exam.
What is the y axis in the curve representing exactly and why the value of the mean is represented by a higher bar than the values bigger than the mean is it only me who found this explanation more confounding 🤔
Wouldn't the standard error of this distribution be sigma/sqrt(n) and not sigma as it says in the video? Sigma is the standard deviation of the population, not the standard deviation of the distribution of sample means.
I believe they meant the standard deviation of the sample mean distribution (aka standard error directly). They didn't explain on how you obtain that standard error which is exactly what you stated (σ/sqrt(n)).
Great video. I really wish people would stop talking about looking up values in a statistical table though. It's 2024 for god's sake!
And FYI, at 5:47 it should say should say "mean of sample means of 48" not "sample mean of 48"; and then maybe "standard deviation of sample means" for clarity.
Heyy ...plz tell me how can I prepare these kind of slides for my presentation kindly guide me have u did it from ppt??
IF the underlying population distribution is NOT NORMAL, and we have samples less than 30. Let's say the samples are size
n = 5. I know the distribution of the sample means will not be normal according to the CLT. However, will the distribution have the same mean as the population mean, and will the variance be equal to the variance of the population divided by 5? Please let me know? thanks?
no and no, gotta either have a normally distributed population or n>30 for those conditions to apply (and it would be divided by the square root of the sample size, not the sample size itself)
@@VaiskHD
Are you sure? I thought no matter how the population is distributed if you take large samples for a population the sample means will be normally distributed
excellent
Thanks!
An alternative solution film or take photo of the différents fish an use a computer algorithm to classify the data
This example was great. However, I don't think you need to increase the sample size to be more precise. Well indeed you will eventually reach the population size and there will be no need of sampling. CLT on the other hand talks about the number of samples. These two are not same.
Jacobson Vista
interesting
Bayer Parkways
This explanation is unnecessarily complicating things. It was hopeless.
Every time I hear profit, I think of Promised Neverland. Any weebs in here that get what I'm saying?
Young Anthony Martin Donna Young Steven
context is dated.
Waao
Eh, not a great example problem.
😢😂
wassup 11 - ITALIAE!!!!!!!!!!!!!!!