Calculating Uncertainty in R Using Partial Derivatives

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In summary, the conversation discusses the process of calculating the theoretical value of R and finding the uncertainty in R using a complicated equation involving trigonometric functions and square roots. The speaker mentions using partial derivatives to simplify the equation and suggests using a program like Matlab or Mathematica for calculations. They also provide a formula for finding the error in a function with multiple variables.
  • #1
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I have a lab where I have to calculate the theoretical value of R using the following equation and then find the uncertainty in R.

R=(xCOS(y))*((-xSIN(y)-SQRT((xSIN(y))^2-2*-9.8*z))/-9.8)
*I know the values of x,y,z and their respective uncertainties.

The problem is that we have only learned basic uncertainty rules (i.e. for multiplication/division you add the %uncertainty, for addition/subtraction you add the absolute uncertainties). This is much more complicated since I have to deal with SIN/COS and square roots. I was searching around and it seems that I have to calculate the partial derivative or differentials. I am not familiar with differentials and I have no idea how to solve this problem. If anyone can offer any help whatsoever it would be greatly appreciated or anywhere where I can find this information.
 
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  • #2
I'm using excel if that makes any difference whatsoever
 
  • #3
questions said:
I was searching around and it seems that I have to calculate the partial derivative or differentials. I am not familiar with differentials and I have no idea how to solve this problem.

You are quite right about using partial derivatives. Don't be scared yet. I agree that you have a complicated expression to start with. I would suggest first simplifying it as much as possible (using trig identities). I assume you know basic differentiation? I really hope so...
When I say "simplify" I mean put it in a form that's less "scary" to differentiate. (derivatives of sin and cos can be found in any table of derivatives).

Example: If you have a function [tex] T=T(f,\lambda,...) [/tex] then the error in T is found by:
[tex] (\delta T)^2 = (\frac{dT}{df})^2(\delta f)^2 + (\frac{dT}{d\lambda})^2(\delta \lambda)^2+(\frac{dT}{d...})^2(\delta ...)^2 [/tex]
where [tex] \delta [/tex] is the error value(s).
 
  • #4
questions said:
I'm using excel if that makes any difference whatsoever

I don't know if Excel can differentiate...Ever used Matlab or Mathematica?
 
  • #5
To calculate the partial derivative [itex]\partial R/\partial x[/itex], differentiate R with respect to x, treating all the other variables as constants. Do likewise for the other partial derivatives.
 
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What is uncertainty?

Uncertainty is the lack of knowledge or precision about a particular measurement or value. It is often expressed as a range of possible values.

Why is it important to calculate uncertainty?

Calculating uncertainty allows us to understand the potential error or variation in our data or measurements. This helps us to assess the reliability and accuracy of our results.

How do you calculate uncertainty?

Uncertainty is typically calculated by taking into account the precision of the measuring instrument and any sources of error or variability in the measurement process. It is often expressed as a percentage or a range of values.

What factors can contribute to uncertainty?

There are several factors that can contribute to uncertainty, including limitations of the measuring instrument, human error, environmental factors, and inherent variability in the system being measured.

How can uncertainty be reduced?

Uncertainty can be reduced by using more precise measuring instruments, minimizing sources of error, and increasing the number of measurements taken. It is also important to carefully analyze and interpret the data to identify any potential sources of uncertainty.

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