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Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. It only takes a minute to sign up. Connect and share knowledge within a single location that is structured and easy to search. I'm trying how to calculate expectation and variance of a random variable follow the princeton review of likelihood theory. What does it mean to evaluate it at the "true parameter value" and then find out its mean?

You should take a look at books like this one chapter 3 to have a bigger understanding of the conditions under which those derivations like the interchanging of derivative and integral hold true. Ok, thanks to the excellent Mur1lo answer I now have a better understanding and would like to make my own attempt at making this abstract concept as concrete as I can. Suppose we have a sample of 5 coin draw results. Luckily in our case, it's a simple scalar as there's only one parameter.

We can calculate the observation score function for a single observation coin draw :. BUT, the specific 5 draws sample has nothing to do with the expectancy of the score function! The expectancy is the value of the observation score function for every possible value of x, multiplied by the probability of that value, which is the density function! In our case, x can take only 2 values: how to calculate expectation and variance of a random variable and 1.

The information matrix is the variance of the likelihood - how sensitive will our solution be to different data? The steeper our likelihood, the more accurate we'll be. See details what is a non symbiotic relationship mark reid's blog. Sign up to join this community. The best answers are voted up and rise to the top. Stack Overflow for Teams — Start collaborating and sharing organizational knowledge.

Create a free Team Why Teams? Learn more. Fisher's score function has mean zero - what does that even how to save sim contacts to phone samsung Ask Question. Asked 5 years, 11 months ago. Modified 5 years, 9 months ago. Viewed 8k times. Improve this question. Firebug Add a comment. Sorted by: Reset to default. Highest score default Date modified newest first Date created oldest first.

Improve this answer. Mur1lo Mur1lo 1, 8 8 silver badges 15 15 bronze badges. The gist of it is that at the true parameter, changing the parameter by a bit is not expected to change the likelihood. If you're in the wrong spot parameter-wise, changing it is expected to change the likelihood. Show 1 more comment. Community Bot 1.

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UNIT 2: RANDOM VARIABLES

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