Question about errors in Numerical Analysis

In summary, the conversation discusses a problem in numerical analysis where a large error occurs when subtracting two almost equal numbers. The error is caused by the limited number of significant digits that can be stored in a "float" and results in a relatively large percentage error. The issue is resolved and the conversation ends with gratitude.
  • #1
evinda
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Hey! I am looking at an exercise in Numerical Analysis and I got stuck.
Why do we have a huge error when we substact two almost equal numbers?
 
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  • #2
evinda said:
Hey! I am looking at an exercise in Numerical Analysis and I got stuck.
Why do we have a huge error when we substact two almost equal numbers?

Hey evinda!

Suppose we calculate $1.000001 - 1$.
In a "float" you can only keep 7 significant digits, so the first number cannot have more reliable digits than it already has.
The accuracy of both numbers is $\pm 0.0000005$.
Or as a percentage: \(\displaystyle \frac{0.0000005}{1} \times 100\% = 0.00005 \%\), which is a pretty small error.The result of the subtraction is $0.000001$, but its accuracy is still about $0.0000005$.
Or as a percentage \(\displaystyle \frac{0.0000005}{0.000001} \times 100\% = 50 \%\)I'd say that is quite a large error relatively speaking. Don't you?
 
  • #3
Great...I got it...Thank you very much! :eek:
 

FAQ: Question about errors in Numerical Analysis

What is Numerical Analysis?

Numerical Analysis is a branch of mathematics that deals with developing numerical methods and algorithms to solve mathematical problems that are difficult or impossible to solve analytically.

What are errors in Numerical Analysis?

Errors in Numerical Analysis refer to the discrepancies between the exact solution to a mathematical problem and the approximate solution obtained through numerical methods. There are various types of errors, including round-off errors, truncation errors, and interpolation errors.

Why are errors in Numerical Analysis important?

Errors in Numerical Analysis are important because they affect the accuracy and reliability of the numerical solutions obtained. It is essential to understand and control these errors to ensure that the results obtained are acceptable and useful.

How are errors in Numerical Analysis managed?

Errors in Numerical Analysis can be managed through various techniques such as using more accurate numerical methods, reducing the step size in iterative methods, and using error-correcting codes.

What are some common sources of errors in Numerical Analysis?

Some common sources of errors in Numerical Analysis include using inappropriate numerical methods, using insufficiently precise computer hardware, and errors in input data or assumptions made in the problem. Human error can also contribute to errors in numerical analysis.

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