if we are given a pdf of 4 values of x with their probabilities in terms of theta, then we find an estimator for the mean theta-hat and then we find the mean square error in terms of theta (should it be in terms of theta?), how can we find if it it mean square consistent. I am unsure because n=4 for my questions so I can't see how it makes sense to consider the limit as n goes to infinity. Please could someone shed some light. Thank you
The first explanation I found that takes the time to expand Bias^2. Thank you!
Love your demonstrations
Thank u 💛
Thank you so much! I spent too much time trying to figure this out and this was so clear.
You're doing a great job, thank you.
2:23 why not distributing expected value E to theta^2???
i dont understand the distributive properties of expectation
@@sophia17965since theta squared is a constant, the expected value of a constant is simply the constant
if we are given a pdf of 4 values of x with their probabilities in terms of theta, then we find an estimator for the mean theta-hat and then we find the mean square error in terms of theta (should it be in terms of theta?), how can we find if it it mean square consistent. I am unsure because n=4 for my questions so I can't see how it makes sense to consider the limit as n goes to infinity. Please could someone shed some light. Thank you
thank you
amazing
Yay!! Awesome