Understanding Probability Density Functions for Beginners

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Discussion Overview

The discussion revolves around understanding probability density functions (pdfs), focusing on their properties, units, and the relationship between pdfs and histograms. Participants explore foundational concepts related to probability and density, as well as specific mathematical definitions and implications.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant questions the units of ##f(x)## in a pdf and why the product ##f \times dx## represents probability rather than just ##f## itself.
  • Another participant suggests thinking of "density" in terms of physical density, comparing it to mass density and discussing the integration process to find mass over an interval.
  • It is proposed that the "units" of a pdf could be described as "probability per unit length" or "per unit area," but the complexity of defining probability in a rigorous manner is acknowledged.
  • A participant expresses confusion about the definition of ##H## in the context of histograms and its relation to the pdf, indicating a lack of clarity in the provided text.
  • One participant expresses frustration over the limited information provided about ##H## and its arguments, emphasizing the need for more context.

Areas of Agreement / Disagreement

Participants appear to have differing levels of understanding regarding the definitions and implications of pdfs and histograms. There is no consensus on the clarity of the definitions or the relationship between the concepts discussed.

Contextual Notes

The discussion highlights limitations in the provided text regarding the definitions and context of terms like ##H## and ##c##, which may affect participants' understanding of the topic.

member 428835
hello all!

i am wondering about probability density functions. i know the area under a pdf gives the probability of an event, but i am having a difficult time seeing this. specifically, given a pdf we have ##\int_a^b f(x) dx## as the probability of an occurrence from ##[a,b]##. what are the units of ##f(x)##? why exactly is ##f \times dx## the probability, rather than just ##f## itself?

please illustrate with a histogram if you can. thanks!
 
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i should add, in the text I'm using we are given that, if ##H(c, \Delta c, N)## where ##\Delta c## is the slot width, ##N## is the number of realizations of the random variable. evidently $$B(c) := \lim_ {\substack{\Delta c \to 0 \\ N \to \infty}}\frac{H(c, \Delta c, N)}{\Delta c}$$

where ##B(c)## is a pdf. can someone help explain this? nothing was really said about ##c## or ##H## other than ##H## is the histogram. i assume ##c## is a random variable?
 
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joshmccraney said:
what are the units of ##f(x)##? why exactly is ##f \times dx## the probability, rather than just ##f## itself?

Think of "density" in terms of physical density - for example, let f(x) be the mass density of a rod given in terms of kilograms per meter at the point x. To find the mass of a rod between two points, you'd do an integration. The value of f(x_0) at the point x_0 is some value of density, not a value indicating mass.

You could say that the "units" of a pdf are "probability per unit length" (or "per unit area" etc.) , but I don't know if anyone has ever worked out a good way for abbreviating all the information that goes along with "probability" in the same system we use for units in physics. To speak of "the probability" of an event unambiguously, you have to define a "sample space" and an algebra of sets of events and a measure defined on that algebra. If we say that a particular formula "is a pdf" then we convey a lot of mathematical conventions with that short phrase. As far as I know, in physics "probability" is a "dimensionless" quantity. From that point of view, the "units" of a pdf are 1 over the unit of measure used on the sample space. .
 
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joshmccraney said:
we are given that, if ##H(c, \Delta c, N)##

You didn't say what H is. You only defined its arguments.
 
thanks for the reply! yea, tho author of the text on states that ##H## is a histogram. nothing more is stated that i haven't already listed...it's pretty annoying.
 

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