What is the name and application of this probability distribution

Click For Summary

Discussion Overview

The discussion centers around identifying a discrete probability distribution presented in a homework context, specifically focusing on its name and potential applications. Participants explore the characteristics of the distribution and clarify its formulation.

Discussion Character

  • Homework-related
  • Debate/contested
  • Technical explanation

Main Points Raised

  • One participant presents a formula for a discrete probability distribution and seeks its name and applications.
  • Another participant suggests that the distribution resembles the Poisson distribution and provides a link to its Wikipedia page.
  • A different participant questions the correctness of the original formula, noting that the standard Poisson distribution includes an exponential decay term.
  • Some participants discuss the role of the normalization factor N in the context of the distribution.
  • There is a correction regarding the exponential term in the Poisson distribution, with participants emphasizing its importance in the formula.

Areas of Agreement / Disagreement

Participants express differing views on the correctness of the original formula and its relation to the Poisson distribution. There is no consensus on the exact formulation, and some participants acknowledge confusion regarding the normalization factor.

Contextual Notes

There are unresolved questions about the correct formulation of the probability distribution, particularly regarding the presence of the exponential term and the role of the normalization constant N. The discussion reflects varying interpretations of the distribution's definition.

Lurco
Messages
3
Reaction score
0
Hi.

In my homework I've encountered a discrete probability distribution of this form:

[tex]f(k,\lambda)=N \frac{\lambda^k}{k!}[/tex]

[tex]k[/tex] is the variable, and [tex]\lambda[/tex] is a parameter. I'm curious what is this distribution - what's its name and where can it be applied. I will be grateful for, for example, redirecting me to the proper wikipedia article. Thanks!
 
Physics news on Phys.org
Lurco said:
Hi.

In my homework I've encountered a discrete probability distribution of this form:

[itex]f(k;\lambda) = \frac{\lambda ^{k} e^{\lambda}}{k!}[/itex]

[tex]k[/tex] is the variable, and [tex]\lambda[/tex] is a parameter. I'm curious what is this distribution - what's its name and where can it be applied. I will be grateful for, for example, redirecting me to the proper wikipedia article. Thanks!

Are you sure you copied the formula correctly? The Poisson distribution is defined by:

[itex]f(k;\lambda) = \frac{\lambda ^{k} e^{-\lambda}}{k!}[/itex]

where [itex]\lambda[/itex] is the rate parameter (expected number of events per unit time), and k is the number of events observed.

In evaluating Poisson noise the question becomes [itex]P(k=N_t)[/itex] but your formula still doesn't look right since it lacks the exponential term.
 
Last edited by a moderator:
I think the number N here is used as a normlization factor.

SW VandeCarr said:
Are you sure you copied the formula correctly? The Poisson distribution is defined by:

[itex]f(k;\lambda) = \frac{\lambda ^{k} e^{-k}}{k!}[/itex]

where [itex]\lambda[/itex] is the rate parameter (expected number of events per unit time), and k is the number of events observed.

In evaluating Poisson noise the question becomes [itex]P(k=N_t)[/itex] but your formula still doesn't look right since it lacks the exponential term.
 
shuxue1985 said:
I think the number N here is used as a normlization factor.

[EDIT]: After reading the wiki page, yes the value depends on lambda not k.

Can't believe I've used this pdf so many times and forgotten it!
 
Last edited:
Thank you all for responding. Yes, the number N stand for the normalization constant, and in the wikipedia article posted by micromass the exponent is exactly the normalization:
[tex]e^{-\lambda},[/tex]

so i does not vary with k.
 

Similar threads

  • · Replies 7 ·
Replies
7
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 4 ·
Replies
4
Views
1K
  • · Replies 10 ·
Replies
10
Views
2K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 29 ·
Replies
29
Views
6K
Replies
2
Views
2K