MHB Cumulative Distribution function in terms of Error function

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The discussion focuses on deriving the cumulative distribution function (CDF) in terms of the error function for non-negative values of x. The error function is defined as an integral involving the exponential function, while the CDF is presented in a different integral form. Participants suggest making a substitution in the CDF to align it with the error function's exponential form. Additionally, recognizing that the error function is an even function is highlighted as a key step in simplifying the problem. The conversation aims to guide the original poster towards a clearer understanding and solution.
TheFallen018
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Hey guys,

I've got this problem I've been trying to solve, but it makes little sense to me. I've tried a few things, but I feel like with each method, I've made no progress, and I haven't been able to make the problem make any more sense to me by trying those things.

Here's the question:

The error function is \begin{align*}\frac{1}{\sqrt{\pi}}\int_{-x}^{x}e^{-t^2} dt\end{align*}
The cumulative distribution function for $x\geq0$ is \begin{align*}\frac{1}{2}+\frac{1}{\sqrt{2\pi}}\int_{0}^{x}e^-\frac{t^2}{2} dt\end{align*}

By making a suitable substitution, find a formula for the cumulative distribution function in terms of the error function when $x\geq0$

The previous question had to do with taking the derivative with respect to x of the error function, so I was thinking I could try integrating that again and use parts of that, but that obviously didn't work. I've lost track of where my thoughts are, so I was hoping someone would be able to point me in the right direction.

Thank you :)
 
Last edited:
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Hi TheFallen018,

Here are a few hints:
  1. Notice that the error function is an even function. Use this fact to find an equivalent integral form for the error function.
  2. Make a substitution in your cumulative distribution function so that $e^{-\frac{t^{2}}{2}}$ becomes $e^{-t^{2}}$ to match the form of the exponential in the error function.
  3. Do a little algebra to combine your answers from Steps 1 & 2 to get an expression for the distribution in terms of the error function.

Let me know if anything requires further clarification.
 
Last edited:

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