How do I convert between cdf and pdf?

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SUMMARY

This discussion focuses on converting cumulative distribution functions (CDF) to probability density functions (PDF) and vice versa. The CDF provided is F(x) = 1 - e^(-αx^β) for x ≥ 0, where α > 0 and β > 0. To derive the corresponding PDF, the chain rule is applied, leading to the differentiation of F(x). For the PDF f(x) = (1 + α)/2 for -1 ≤ x ≤ 1, the integration process is outlined to find the CDF, emphasizing that F(1) must equal 1, indicating a uniform distribution.

PREREQUISITES
  • Understanding of cumulative distribution functions (CDF)
  • Knowledge of probability density functions (PDF)
  • Familiarity with differentiation and integration techniques
  • Basic concepts of uniform probability distributions
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  • Study the application of the chain rule in calculus
  • Learn about uniform distributions and their properties
  • Explore integration techniques for continuous functions
  • Research the relationship between CDF and PDF in probability theory
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Statisticians, data scientists, mathematicians, and anyone involved in probability theory and statistical analysis will benefit from this discussion.

scot72001
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hi
i'm looking for help when going from a cdf function:
F(x) = { 1- e^-αx^β x ≥ 0, α>0, β>0
{ 0 x < 0

to getting the corresponding pdf

also i am looking to do the opposite(pdf to cdf)
for:
f(x) = { (1 + α)/2 for -1 ≤ x ≤ 1, -1 ≤ α ≤ 1
{ 0 otherwise

i'm unsure as to how to integrate and differentiate these parts.
can you help please

thanks
michael
 
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scot72001 said:
hi
i'm looking for help when going from a cdf function:
F(x) = { 1- e^-αx^β x ≥ 0, α>0, β>0
{ 0 x < 0
Is that [itex]1- e^{-\alpha x^\beta}[/itex] rather than [itex]1- e^{-\alpha}x^\beta[/itex]? If so, let [itex]u= \alpha x^\beta[/itex] and use the chain rule: df/dx= (df/du)(du/dx).

to getting the corresponding pdf

also i am looking to do the opposite(pdf to cdf)
for:
f(x) = { (1 + α)/2 for -1 ≤ x ≤ 1, -1 ≤ α ≤ 1
{ 0 otherwise
Then integrate: [itex]F(x)= \int_{1}^x (1+\alpha)/2 dt[/itex] for [itex]-1\le x\le 1[/itex]. That should be easy. Of course, F(1) must be 1. That will require that [itex]\alpha[/itex] have a specific value. In fact, since f(x) is a constant, this is a uniform probability and you should be able to do it without integrating.

i'm unsure as to how to integrate and differentiate these parts.
can you help please

thanks
michael
 

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