Calculating {erf}(x) Without Computers?

  • Thread starter LM741
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In summary, the conversation revolves around calculating the error function, erf(x), and whether it is possible to evaluate it without computational techniques. The participants discuss the use of Matlab and other methods such as numerical integration and Taylor series. It is mentioned that there is a closed form expression for large values of x. A link is also provided for more information.
  • #1
LM741
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Hi guys...
don't suppose anybody knows how to calculate the error function - erf(x)

I know Matlab can calculate it - but is it possible to evaluate it without computational techniques (i.e. using computers)?

[tex] {erf}(x) = \frac{2}{\sqrt{\pi}}\int_0^x e^{-t^2} dt.[/tex]

Would appreciate any feedback.

thanks.

The link below will direct you to a website where the equation can be viewed...

http://images.planetmath.org:8080/cache/objects/6429/l2h/img2.png
 
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  • #2
If you mean "Is there an elementary anti-derivative" that can be evaluated directly, the answer is no. The only way to evaluate erf(x) is to do a numerical integration.
 
  • #3
thanks...
by numerical integration do you mean applying Tayler Series and expansions like that?
 
  • #4
I was thinking more of Simpson's rule.
 
  • #5
LM741 said:
thanks...
by numerical integration do you mean applying Tayler Series and expansions like that?

actually, with a computer program to calculate the terms and summation, that is what they do. one thing is that there is a nice closed form expression for the erf(x) for large x.

see http://mathworld.wolfram.com/Erf.html for some detail.
 
  • #6
thanks guys!
 

1. What is the definition of {erf}(x)?

The error function, denoted as {erf}(x), is a mathematical function that measures the deviation between a true value and a measured or estimated value. It is commonly used in statistics, physics, and engineering.

2. Why is it important to be able to calculate {erf}(x) without computers?

While computers can quickly and accurately calculate {erf}(x), it is still important to know how to calculate it by hand. This allows for a better understanding of the underlying concepts and can be useful in situations where computers are not available or when a quick approximation is needed.

3. What is the formula for calculating {erf}(x) without computers?

The formula for calculating {erf}(x) without computers is: {erf}(x) = (2/√π) * ∫x0 e-t2 dt

4. Are there any tricks or shortcuts for calculating {erf}(x) without computers?

Yes, there are some tricks and shortcuts that can make calculating {erf}(x) without computers easier. For example, for small values of x, the value of {erf}(x) can be approximated using the first few terms of its Taylor series. Additionally, there are tables and charts available that can help with calculations.

5. How is {erf}(x) used in real-world applications?

{erf}(x) has many practical applications, including in statistics for calculating the probability of a normally distributed variable falling within a certain range. It is also used in physics and engineering for modeling and analyzing error and uncertainty in measurements and calculations.

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