Mam the concept is very tricky but u made the whole central limit theorem as easy as eating Really liked it video and shared with other Mam keep on making such informational videos for the betterment of students
So which one is true Central Limit Theorem means that for sufficiently well behaved population distribution that the sample means will be consistent with a normal distribution. Large enough population, the population distribution will be consistent with a normal distribution
Please check sampling playlist on my channel, it’s there You will find both videos separately for conceptual understanding and a 3rd video describing difference between them.
Or central limit theorom means that for sufficiently many elements in our sample, and for sufficiently well behaved population distribution that the sample means will be consistent with a normal distribution
According to CLT, if population is not normal but sufficiently well behaved, sampling distribution of the sample mean will be approximately normal (condition here is sample size should be sufficiently large) Hope it is helpful!! Stay Connected!!
0:35 min EXAMPLE
3:08 min MEANING
4:10 min ASSUMPTIONS
5:10 min IMPORTANCE
PLEASE LIKE AND SHARE THE VIDEO IF YOU FIND IT WORTH
I really like your explanation and conceptual clarity. You make the concepts so simple to understand
Very easy explanation..thanku mam 👍👏
Mam the concept is very tricky but u made the whole central limit theorem as easy as eating
Really liked it video and shared with other
Mam keep on making such informational videos for the betterment of students
Thank You ☺️
Stay Connected!!
@@dr.sumeetbakshi thanku madam
Very well explained mam
So which one is true
Central Limit Theorem means that for sufficiently well behaved population distribution that the sample means will be consistent with a normal distribution.
Large enough population, the population distribution will be consistent with a normal distribution
Can you illustrate mutisage cluster and cluster sampling
Please check sampling playlist on my channel, it’s there
You will find both videos separately for conceptual understanding and a 3rd video describing difference between them.
Or central limit theorom means that for sufficiently many elements in our sample, and for sufficiently well behaved population distribution that the sample means will be consistent with a normal distribution
According to CLT, if population is not normal but sufficiently well behaved, sampling distribution of the sample mean will be approximately normal (condition here is sample size should be sufficiently large)
Hope it is helpful!!
Stay Connected!!