Applying the central limit theorem to find probability example 1

In this video, we demonstrate how to use the central limit theorem to find a probability. Ultimately, the central limit theorem allows us to convert the problem into a problem of finding area under the normal curve. The only change is that we use the standard error instead of the standard deviation.

[esfasdasasdasdas]

Thank you! By far this was the clearest explanation I could find.

[christian_uu]

you have no idea how helpful this was, thank you so much!

[prettyone]

real professor indeed, my Lecturer only lecture us and rap at the same time so I couldn't get the concept well but per your explanation I've been able to figure it out well, Please Prof. Do more videos and make more examples for us pls 🥺🥺🥺 and if You've your private page that you do tutorials on all statistics topic and also all economics topic please kindly add me up 🥺🥺🥺🥺 am pleading 🙏🏻🙏🏻🙏🏻

[dipankarbanerjee]

Thanks Prof.🙏 lots of love from India ❤❤

[davidmoretz]

One of the best explained examples--thank you!

[AndyIsHereBoi]

this was the most helpful one that i have ever found

[rababshahzad]

THANKYOU SOOO MUCH, I COULDNT FIND ANY THING USEFUL BEFORE THIS!

[coopermau]

I wanna be this guys friend. Saving my stats grade on video at a time lets go!

[sajimathew]

thank you, sir !! with love from India

[DaPower]

God I wish literally any of my professors could teach this well

[zakarias]

Thank you so much for the enlightening explanation!
However, I still can not understand why you directly applied the CLT on the 32 women, while this theorem assumes the calculation of the mean of the sampling distribution. Here is an example:
Maybe we need to observe the mean of n=5(or more) of the 32 women(with replacement), and we do it repeatedly 100 or 1000 times. Then we can apply the CLT. Otherwise, the sample age at first marriage of the 32 women might not be normally distributed.
Plz, correct me if I am wrong🙏.

[randym]

Thanks for the wonderful explanation. It would be very helpful if you could elaborate how did you derive the standard deviation of the normal curve (for the average) to be 4/sqrt(n)

[stekichung]

great explanation, thank you so much for making this!

[shazmeenshakeel]

thank you so much, this was very helpful

[bobmcbobface]

So we’re basically integrating a Gaussian?

[aitothechamp]

If we are trying to create our own problem, what situations would this apply to? This is only when we have the population mean and population st dev, correct? Like, what if I have all of the sample data, and want to find the probability that the sample data meets a certain criteria (xbar). So in this case I have the literal sample mean and literal sample st dev, but don't have the population mean or population st dev.

[aliteralnormalguy]

Thank you so much sir! I thought I was a goner then I saw this video. Thanks again!

[therice]

Can you explain why standard deviation divide by square root of n?

[sanchitakanta]

The average for a normal distribution lies at the middle with a z value of 0.
Isn't it?
How can it lie between 26 and 27.

[luisrodrigueziii]

Hello my friend. Why did you divide the given standard deviation by the square root of 32?