Thanks for uploading all this content. I am about to begin my masters in data science soon and I was trying to grasp some math theory which is hard for me coming from a CS Background. Your videos make it so simple to digest all these topics.
Nice videos. I'm now preparing for my masters and it will be quite useful; the connection between CRLW and the standard error of the estimates by MLE makes this very nice.
Shouldn’t the variance of the first data point be (X1-Xbar)/1 or (X1-Xbar)/0 which is just 1 as we want the variance of just first data point whereas sigma^2 is the variance of the whole sample?
No, sigma^2 is the variance of each individual data point because it’s the variance of the entire distribution. You’re getting a little mixed up - realized data values don’t have variances, I’m talking about the first data point being a random variable that has variance sigma^2. Nothing in this video is about calculating sample variances so X-bar and the sample variance are not involved at all.
Just to be clear, the “First data point X1” refers to one random value from a sample. We are checking how good of an estimator just one value from a sample is as opposed to the X-bar which is the mean of that sample?
Yes, basically, but keep in mind we are never talking about any particular sample. We are just comparing samples of size one, which have variance sigma^2 and samples of size n, where X-bar has variance sigma^2/n
I'm so grateful for all the videos you make that inspire our curiosity!
Thank you! :)
That video is gold for every stats student! Thanks a lot for this amazing content!
Exactly the kind of video I was looking for, Perfect explanation.
Thanks for uploading all this content. I am about to begin my masters in data science soon and I was trying to grasp some math theory which is hard for me coming from a CS Background. Your videos make it so simple to digest all these topics.
perfect and easiest explanation in utube....thanku so much sir it is really helpful
Nice videos. I'm now preparing for my masters and it will be quite useful; the connection between CRLW and the standard error of the estimates by MLE makes this very nice.
Fantastic video... preparing for IIT JAM MS
Super helpful video! Thank you:)
Brilliant!
Many thanks 🙏
Shouldn’t the variance of the first data point be (X1-Xbar)/1 or (X1-Xbar)/0 which is just 1 as we want the variance of just first data point whereas sigma^2 is the variance of the whole sample?
No, sigma^2 is the variance of each individual data point because it’s the variance of the entire distribution. You’re getting a little mixed up - realized data values don’t have variances, I’m talking about the first data point being a random variable that has variance sigma^2. Nothing in this video is about calculating sample variances so X-bar and the sample variance are not involved at all.
Just to be clear, the “First data point X1” refers to one random value from a sample. We are checking how good of an estimator just one value from a sample is as opposed to the X-bar which is the mean of that sample?
Yes, basically, but keep in mind we are never talking about any particular sample. We are just comparing samples of size one, which have variance sigma^2 and samples of size n, where X-bar has variance sigma^2/n
Got it. Thanks so much for taking the time out to answer my queries. You are very kind.
Soo good! Didn't get it in class at all