Probability Function of X: Solutions & Steps

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Discussion Overview

The discussion revolves around the probability function of a discrete random variable X, specifically focusing on finding the normalization constant c and the moment generating function. Participants explore the implications of the function being a probability density function versus a probability mass function, and they engage in deriving solutions for various parts of the problem.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • Some participants propose that the probability function is defined as f(x) = c e^(-x) for x = 1, 2, 3, ...
  • One participant suggests that the term "probability density function" is more precise, prompting a discussion about the nature of the function.
  • There is a claim that the normalization constant c can be found by solving the equation involving a geometric series, leading to the expression C = 1/(1 - e^(-1)).
  • Another participant questions the validity of the derived value of c, stating that their own calculations lead to a different conclusion.
  • Some participants express uncertainty about the domain of x, questioning why it does not include non-integer values.
  • One participant mentions that using integration to find the area under the curve is appropriate for probability density functions, contrasting it with the summation method used for discrete functions.
  • There is a suggestion that the answer for part (a) should be e^(-1) rather than 1/e.
  • One participant notes the potential for typographical errors in the problem statement, indicating possible confusion in the discussion.

Areas of Agreement / Disagreement

Participants express differing views on the correct value of c and the interpretation of the function as a probability density function versus a probability mass function. There is no consensus on the correct approach or solution, and the discussion remains unresolved.

Contextual Notes

Participants highlight limitations in the problem statement, including potential typographical errors and the ambiguity regarding the domain of x. The discussion also reflects uncertainty about the appropriate methods for calculating probabilities and expectations.

tee yeh hun
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Let the probability function of X be given by
f(x)= c e-x, x=1,2,3,...
(a)Find the value of c.
(b) Find the moment generating function of X,

Solutions (a) e-1
(b) (e-1) [ (et-1)/(1-et-1)]

Can anyone shows the steps?
 
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tee yeh hun said:
Let the probability function of X be given by
f(x)= c e-x, x=1,2,3,...

It is more precise to say "probability density function".

(a)Find the value of c.

Solve the equation \sum_{x=0}^{\infty} Ce^{-x} = 1 for C.

C \sum_{x=0}^{\infty}e^{-x} = 1

(The sum is a geometric series with ratio e^{-1} )

Can you do the rest of the steps?


(b) Find the moment generating function of X,

M(t) is expected value of e^{tx}.

M(t) = \sum_{x=0}^\infty ( e^{tx} C e^{-x })

= C \sum_{x=0}^\infty (e^{t-1})^x

The sum is a geometric series with ratio e^{t-1}

Solutions (a) e-1

I got C = \frac{1}{1 - e^{-1}}

Is that the same thing?.

(b) (e-1) [ (et-1)/(1-et-1)]

I got \frac{C}{ 1 - e^{t-1}}
 
thank you for the showings, appreciate it. Yes i can do the rest of it.
 
Last edited:
Stephen Tashi said:
I got C = \frac{1}{1 - e^{-1}}

Is that the same thing?.


Here it goes,
It stated that the domain of x is from 1 to infinity(I am not sure why they didn't include 1.1, 2.3 , 5.89 these kind of numbers)

But unfortunately, if we are discussing probability density function, we use integral to find out where are the area covers.

∫Ce-xdx = 1 [1,infinity)

the integral or summation method is the same idea actually.

Then we will find out that our C is which is 1/(e^1)

but for all no reason the answer of (a) is e-1 not e the power of -1
 
Last edited:
the whole question is as follow
Let the probability function of X be given by
f (x) = ce-x , x = 1, 2, 3, ….
(a) Find the value of c.
(b) Find the moment generating function of X.
(c) Use the result obtained from (b) to find E(X).
(d) Find the probability generating function of X.
(e) Verify that E(X) obtained using probability generating function is same as in (c).


Answers:
answer1.jpg
 
Perhaps there is a typographical error in the problem. Perhaps there is more than one typographical error.
 

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