CDF of a variable with a negative exponent in its PDF

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SUMMARY

The discussion centers on the calculation of the cumulative distribution function (CDF) for a random variable X with a piecewise probability density function (PDF). The initial CDF calculations yielded negative values and discontinuities, which were resolved by correctly applying the integral of the PDF. The final CDF is defined as F(x) = -2/(3x²) for 1≤x<2 and F(x) = x²/24 for 2≤x≤4, resulting in a valid, increasing function that ranges from 0 to 1. The participant learned that proper integration of the PDF is crucial for accurate CDF computation.

PREREQUISITES
  • Understanding of probability density functions (PDFs)
  • Knowledge of cumulative distribution functions (CDFs)
  • Familiarity with integration techniques in calculus
  • Experience with piecewise functions
NEXT STEPS
  • Study the properties of cumulative distribution functions (CDFs)
  • Learn about piecewise probability density functions (PDFs)
  • Explore integration techniques for calculating CDFs from PDFs
  • Investigate common pitfalls in probability calculations
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Statisticians, data scientists, and students studying probability theory who seek to understand the correct computation of cumulative distribution functions from probability density functions.

jimbobian
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Ok, this one's got me stumped!

Let's take as an example the probability density function for a random variable X so that:

f(x) = \frac{4}{3x^{3}} 1≤x<2
f(x) = \frac{x}{12} 2≤x≤4
f(x) = 0

So the CDF for this variable comes out as:

F(x) = \frac{-2}{3x^{2}} 1≤x<2
F(x) = \frac{x^{2}}{24} 2≤x≤4

So how can the CDF be negative for 1≤x<2, the CDF is P(X≤x), so to my mind that makes no sense. And secondly I have never seen a CDF with a discontinuity like in this one. At x=2, it jumps from -1/6 to 1/6

This made me think that I should ignore the negative sign in the CDF for 1≤x<2, but then for 1≤x<2 F(x) is a decreasing function, how can that make sense?

Someone enlighten me... please!
 
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Ok I've figured out why the minus sign shouldn't have been there, I forgot that what you actually do to find the CDF is:

\int_{-∞}^{x} p(t)dt

Which sorts out the minus sign, other problem still remains?

EDIT: I'm talking rubbish this hasn't fixed a thing!

EDIT2: Turns out it fixed both problems. CDF is now a lovely increasing function that starts at 0 and ends at 1. Turns out I'd been doing an incorrect short cut on CDFs and never noticed because it has never not worked until tonight!
 
Last edited:

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