thanks for all !!!! You uploaded it the day of my birthday !!!! Even if i come from Ivory Coast , i understood your explanation !!! Thanks a lot !!!! ^_^
Hey, thank you for sharing this. At 3:28, you've referred to X-bar as mu and then used that mu = a*theta/a+1. But we used that equation to relate theta-hat and X-bar already, as X-bar = a * theta-hat/a+1. Substituting mu as a*theta/a+1, makes this entire calculation trivial and hence the proof incorrect, right? Easier example to help follow my argument: We define A = 3B + 2, Now we want B-hat as our estimator and see if its unbiased. So we write B-hat = (A-2)/3. Setting expectations on both sides, we get E(B-hat) = (E(A) - 2)/3. But E(A) = 3*E(B) + 2, from our 1st equation. Now if I substitute that, I get E(B-hat) = E(B) and hence B is an unbiased estimator. Is the above logic correct? If yes, then can we say that A and B are related using a linear map M: B->A, then B is always an unbiased estimator for A?
Notice that another x is being multiplied therefore you can.employ laws of indices, ie same base and since they are being.multiplied we add the powers, x has a power of 1 and the other x has a power of a-1, so in adding the power it's a-1+1 which leads to just a so that's why it becomes x^a and the original x^a-1 disappears
Q: Find estimator of parameter 'lemda' of the poison distribution by method of moments. Ans: est. of lemda' = m ; where m is sample moment ( Plz reply)
You just explained in 3 minutes what my lecturer couldn't explain in 1 hour and 30 minutes. Thanks a lot.
You're a liar😢
Well another 3 min video that is better than my professor’s three pages of notes
The 8-bit music at the end makes me feel like I leveled up after having watched.
I did make it to the end. Thank you. You're the real MVP for Making it this simple to understand :)
thanks ^_^
A sample, typical and explicit example is tremendous useful. Thank you.
Beautiful video! You made this concept so much easier and I was really stuck on it!
wow i wish stats instructors explained this like you did
thanks for all !!!!
You uploaded it the day of my birthday !!!!
Even if i come from Ivory Coast , i understood your explanation !!!
Thanks a lot !!!!
^_^
Great example and explanation!
Hey, thank you for sharing this. At 3:28, you've referred to X-bar as mu and then used that mu = a*theta/a+1. But we used that equation to relate theta-hat and X-bar already, as X-bar = a * theta-hat/a+1. Substituting mu as a*theta/a+1, makes this entire calculation trivial and hence the proof incorrect, right?
Easier example to help follow my argument:
We define A = 3B + 2, Now we want B-hat as our estimator and see if its unbiased.
So we write B-hat = (A-2)/3. Setting expectations on both sides, we get E(B-hat) = (E(A) - 2)/3. But E(A) = 3*E(B) + 2, from our 1st equation.
Now if I substitute that, I get E(B-hat) = E(B) and hence B is an unbiased estimator.
Is the above logic correct? If yes, then can we say that A and B are related using a linear map M: B->A, then B is always an unbiased estimator for A?
no you're the real mvp!!
liked subscribed and rang notification bell. Godly explanation
thank you (.❛ ᴗ ❛.)
Nice and simple :)
You are my savior
THANK YOU!
muchas gracias
Nice video
Is there a difference in the workings if a is unknown?
Meaning that, yes the MM is an unbiased estimator or the sample given (sigma)? Because is or isn't the MM a biased estimator for the sample mean?
holy shit thank you for making this
بارك الله فيكم وجزاكم الله خير الجزاء
Thanks a lot!!
Pls ma, I need an estimator of tither from that distribut using the method of maximum likelihood. Thanks
How do you write E(Xbar)=a.theta/a+1 ???? in case of unbiased estimate at 3:30 min
omg thank you so much!
wat if expected value of theeta delta was not equal to theta?
Is there any name for this distribution? I've been looking for a similar one, where theta is fixed to one, and we're estimating "a"
This is a beta distribution where b = 1.
Your sound when you're talking is like to the song " happy birthday to you" as " a theta times x" 😅😅😅
Great work keep going 🌹
Why did she integrate the x* first Moment
thank you a loooooooooot
you're welcomeeeeeeeeeeeee :)
When would it make sense to use the summation notation for expected value vs. the integral notation?
Summation notation is for discrete distributions, integration notation is for continuous distributions
Where does the *x^a-1 (from the p.d.f) disappear to??
Notice that another x is being multiplied therefore you can.employ laws of indices, ie same base and since they are being.multiplied we add the powers, x has a power of 1 and the other x has a power of a-1, so in adding the power it's a-1+1 which leads to just a so that's why it becomes x^a and the original x^a-1 disappears
Can u pls suggest me a book having these kind of problems which would be very much helpful for me??
ik how to solve it, but not seeing its application will make me forget it sooner
Wow
I suppose someone who like my comment just now is going to have the statistic test today🗿
Hi, I would like to ask how do you calculate the confidence intervals of the estimators.
henlo from 2022, for point estimators you don't count them, you only count them for the interval method
Brilliant video , but it's meant for people that are learning the topic so you need to slow it down a bit ! Nevertheless extremely helpful
put 0.75 speed, lol
how to calculate the second moment!?
Time to do the ASSinment, oh wait, let me copy ur method first:(
Q: Find estimator of parameter 'lemda' of the poison distribution by method of moments. Ans: est. of lemda' = m ; where m is sample moment ( Plz reply)
why are you integrating only upto theta
we're integrating x (i forgot to write dx at the end) and we're given in the problem that x is from [0, theta]
Because those are the bounds of the pdf if you look at the original problem
I swear i would marry you right now if i knew you. Exactly what i was looking for.
What about her consent
Face Reveal
Put to 0.75 or 0.5 speed
Helpful, but WAY too fast.
put speed at 0.25
too fast!!!!😂