Numerical Analysis, sensitivity root finding.

In summary, the conversation discussed using the Sensitivity Formula to make a prediction for the nonzero root of the function f(x) = x^n - ax^(n-1) + epsilon x^n, as well as finding the nonzero root and comparing it to the prediction. The Sensitivity Formula for Roots was mentioned, as well as the equation for f'(x). The attempt at a solution involved finding the constant A and plugging it into the sensitivity root to make a prediction for the nonzero root. However, there were some uncertainties in the approach and further help was requested for finding and comparing the nonzero root.
  • #1
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Homework Statement



[itex]Let f(x) = x^{n} - ax^{n-1},\: and \: set\: g(x) = x^{n} \\
(a) \: Use\, the\, Sensitivity\, Formula\, to\, give\, a\, prediction\, for\, the\, nonzero\, \\
root \, of\,\; f_{\epsilon }(x) = x^{n} -ax^{n-1} + \epsilon x^{n} \, for\,small\,\epsilon.\\
\\ (b) \: Find \, the \, nonzero \, root \, and \, compare \, with \, the \, prediction. [/itex]

Homework Equations



Sensitivity Formula for Roots:
[itex]\Delta r \approx -\frac{\epsilon g(r)}{f'(r)}[/itex]

[itex]f'(x) = x^{n-2} (a + xn - an)[/itex]

The Attempt at a Solution



Some thoughts, and tries...

One of the roots for f(x) (without the g(x) and Epsilon) is obviously the constant A.
[itex]a = \frac{x^{n}}{x^{n-1}}[/itex]

So if I now plugg terms into the sensitivity root

[itex]
\Delta r \approx -\frac{\epsilon a^{n}}{x^{n-2} (a + an - an)}
\\
\Delta r \approx - \epsilon \frac{a^{n}}{a^{n-1}}
[/itex]

So a prediction of the nonzero root would simply then be

[itex]r + \Delta r
\\
nonzero root \approx a - \epsilon \frac{a^{n}}{a^{n-1}}
[/itex]

Would that be correct?
 
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  • #2
Also, for b) I am not sure how to find the nonzero root and compare it with my prediction. Any help would be great! Thanks in advance.
 

FAQ: Numerical Analysis, sensitivity root finding.

1. What is numerical analysis?

Numerical analysis is a branch of mathematics that deals with the development, analysis, and implementation of algorithms for solving mathematical problems using numerical methods. It involves using computers to approximate solutions to mathematical problems that cannot be solved analytically.

2. Why is numerical analysis important?

Numerical analysis is important because it allows scientists and engineers to solve complex mathematical problems that arise in real-world applications. It also provides a way to evaluate the accuracy and stability of numerical methods, ensuring reliable results.

3. What is sensitivity analysis in numerical analysis?

Sensitivity analysis is a technique used to determine how sensitive the output of a mathematical model is to changes in the input parameters. It involves varying the input parameters within a specified range and observing the effect on the output.

4. What is root finding in numerical analysis?

Root finding is the process of finding the values of a variable that make a given mathematical equation or function equal to zero. This is often done using numerical methods such as the bisection method, Newton's method, or the secant method.

5. How does numerical analysis help in scientific research?

Numerical analysis plays a critical role in scientific research by providing tools and techniques to solve complex mathematical problems that arise in various fields such as physics, engineering, and economics. It also allows scientists to analyze and interpret large sets of data and make accurate predictions using numerical models.

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