Consider a random sample n from a population

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Discussion Overview

The discussion revolves around finding the maximum likelihood estimator for a parameter p based on a random sample from a population with a specified probability distribution. The focus is on the likelihood function derived from the distribution f(x,p) = p^x (1-p)^(1-x) for binary outcomes x=0,1.

Discussion Character

  • Homework-related
  • Mathematical reasoning

Main Points Raised

  • Post 1 presents the problem of finding the maximum likelihood estimator for p given the probability distribution.
  • Post 4 provides the likelihood function and suggests breaking it into two factors based on the values of x.
  • Posts 2 and 3 express difficulty in starting the problem and request examples or guidance for a starting point.

Areas of Agreement / Disagreement

Participants express varying levels of understanding and readiness to engage with the problem, with some seeking clarification and examples, indicating a lack of consensus on how to proceed.

Contextual Notes

Some participants may be missing foundational assumptions or specific examples that could aid in understanding the problem. There is also an indication of unresolved steps in the mathematical reasoning process.

TomJerry
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Problem: Consider a random sample n from a population with probability distribution f(x,p) that depends on parameter p. Find the maximum likelihood estimator for p when

f(x,p) = p^x (1-p)^1-x for x=0,1
 
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So you've tried...?
 
statdad said:
So you've tried...?

I m having difficulty starting , can you show me an example which is near to this or related to this . I just need a starting point .
 
The likelihood function is

[tex] L(p \colon x_1, x_2, \dots, x_n) = \prod_{i=1}^n p^{x_i} (1-p)^{1-x_i}[/tex]

Break the product into two factors, one in which [tex]x_j = 0[/tex], the other in which [tex]x_j = 1[/tex], and see what the products look like.
 

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