-aux.09.Probability distribution

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Discussion Overview

The discussion revolves around calculating the expected value, denoted as $$E[X]$$, from a given probability distribution table. The context is primarily homework-related, focusing on understanding the concept of expected value in probability theory.

Discussion Character

  • Homework-related, Mathematical reasoning

Main Points Raised

  • One participant expresses uncertainty about what $$E[X]$$ represents.
  • Another participant provides a definition of expected value from Wikipedia, explaining it as a weighted average and emphasizing the requirement that the sum of probabilities equals one.
  • A subsequent reply reiterates the definition of expected value and demonstrates the calculation, arriving at a result of 2.45.

Areas of Agreement / Disagreement

There is no explicit disagreement among participants regarding the definition or calculation of $$E[X]$$, but the initial uncertainty expressed by one participant indicates a lack of understanding that is addressed by others.

Contextual Notes

The discussion does not address potential limitations or assumptions in the calculation process, nor does it explore any alternative methods for finding expected value.

karush
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from probability distribution table

$$x\ \ \ P(X=x)$$
$$1\ \ \ 0.3$$
$$2\ \ \ 0.15 $$
$$3\ \ \ 0.35 $$
$$4\ \ \ 0.2 $$

find $$E[X]$$

I don't know what $$E[X]$$ is
 
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Re: probability distribution

Wikipedia defines it as:

$$E[X]=\sum_{k=1}^n\left(x_kp_k \right)$$

You can also think of it as a weighted average since we must have:

$$\sum_{k=1}^n\left(p_k \right)=1$$

So, you essentially want to find the product of each pair, and then sum them all up. What do you find?
 
Re: probability distribution

MarkFL said:
Wikipedia defines it as:

$$E[X]=\sum_{k=1}^n\left(x_kp_k \right)$$

You can also think of it as a weighted average since we must have:

$$\sum_{k=1}^n\left(p_k \right)=1$$

So, you essentially want to find the product of each pair, and then sum them all up. What do you find?
$$
(1x0.3)+(2x0.15)+(3x0.35)+(4x0.2)=2.45$$

that was easy!
 
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