Problems with propagation of error for multiple variables

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SUMMARY

The discussion centers on the propagation of error in multi-variable functions, specifically addressing the use of vector-distance methods to calculate error vectors based on independent basis errors. The total differential is highlighted as a critical concept for understanding infinitesimal changes in functions relative to their variables. Caution is advised regarding the limits set on triangle quantities, as improper delta values can lead to significant errors, especially in functions with erratic behavior. The importance of analyzing higher-order derivatives in numerical analysis is emphasized for accurate error assessment.

PREREQUISITES
  • Understanding of total differentials in multi-variable calculus
  • Familiarity with vector-distance methods for error calculation
  • Knowledge of first and higher-order derivatives
  • Basic principles of numerical analysis and differential equations
NEXT STEPS
  • Research the application of total differentials in error propagation
  • Study vector-distance methods for calculating error in multi-variable functions
  • Learn about higher-order derivatives and their significance in numerical analysis
  • Explore resources on error analysis in the context of differential equations
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Mathematicians, engineers, and data scientists involved in error analysis and numerical methods, particularly those working with multi-variable functions and seeking to improve their understanding of error propagation techniques.

bobey
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please help by telling me whether my approach to solve the problems are right or wrong. please refer to the ATTACHMENT for the questions and my approaches...

your help is highly appreciated!
 

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Hey bobey.

Your approach seems like you are using a vector-distance based on finding the length of the sum of all independent basis "errors".

The total differential of a multi-variable function describes the infinitesimal change of that function given the infinitesimal changes of all the variables with respect to its derivatives.

What you are doing looks good, but the only thing I would caution you about is what limits you put on the triangle quantities (i.e. the fixed deltas not the infinitesimal values).

Using a small enough value for the triangle delta's of your independent variables should always be OK, but if the function is changing wildly over some region, your errors will be way off. To look at whether this is the case you see how many first derivatives the function has (if any) that are equal to zero and also how the function behaves around your point (whether its derivative suddenly gets really high or really low just after your point).

The method though (calculating the error vector and finding its length) is a sound approach, but the important thing to be aware of is how local this information is and if it's not local (i.e. the stuff that I talked about above happens) then you need to re-consider looking at more global information like later derivatives at that point.

Looking at later derivatives is exactly what is done in numerical analysis when you get the "crazy functions" that have the potential to go wild and if you are interested in error analysis to take into account this behaviour, get some material on numerical analysis and differential equations.
 

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