Solve Uncertainty in "An Introduction to Error Analysis" by John R Taylor

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In summary, the conversation discusses an example from a book about error analysis and the proper way to calculate the uncertainty in a calculation. The example initially uses a formula (3.8) that assumes correlated errors, but the person questioning suggests using the formula (3.9) for uncorrelated errors. They then realize that the factor of 2 from (3.9) cancels out the factor of 2 in (3.8), making the original calculation correct. The conversation also touches on the proper notation for error values.
  • #1
NicolaiTheDane
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This isn't a homework question, but instead a question about an example in a book I'm reading, in prep for next semester. As such using the posting template is a bit of a miss. Hope that can be forgiven.

1. Homework Statement


I'm reading "An Introduction to Error Analysis" by John R Taylor during my spring vacation as brush up for my next semester. I encountered an example that doesn't make sense to me though. It goes through teaching 3 rules as follows:

upload_2018-8-17_14-8-6.png
(3.8)
upload_2018-8-17_14-8-16.png
(3.9)
upload_2018-8-17_14-8-35.png
(3.10)

Now the example it gives is as follows (leaving out units for ease):

##t = 1.6\pm0.1##

##h = 46.2\pm0.3##

Now it calculates ##g = \frac{2*h}{t^2}## and more importantly its uncertainty as follows:

$$\frac{\delta g}{g}=\frac{\delta h}{h}+2*\frac{\delta t}{t} = 0.007+2*0.063 = 0.133$$

as justifed by 3.8 and 3.10. However here is my problem; What about 3.9?

The Attempt at a Solution



As far as I can see, the example completely forgets about the factor 2. With 3.9 in mind, ##x = \frac{h}{t^2}## shouldn't it be:

$$\frac{\delta g}{g}=2*\left(\frac{\delta h}{h}+2*\frac{\delta t}{t}\right)$$

What am I missing?
 

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  • #2
Honestly, you should not be using 3.8 because it essentially makes the assumption that all the errors are correlated (which may be conservative, but usually not the case). If the errors are uncorrelated, it would be more appropriate to add the relative errors in quadrature.

However, given 3.8-10: No, there should not be a factor of 2. What is given in 3.9 is ##\delta q##, not ##\delta q/q##. The factor of 2 from ##\delta q## cancels the factor of 2 from ##q##.

Edit: To expand on that, 3.9 states ##\delta q = |B| \delta x## and by definition ##|q| = |B| |x|## and therefore
$$
\frac{\delta q}{|q|} = \frac{|B|\delta x}{|B| |x|} = \frac{\delta x}{|x|}.
$$

Also, do not write ##\delta * x##, it is ##\delta x## which is the error in ##x##. The ##\delta## and the ##x## are part of the same symbol representing the error in ##x##.
 
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  • #3
Orodruin said:
Honestly, you should not be using 3.8 because it essentially makes the assumption that all the errors are correlated (which may be conservative, but usually not the case). If the errors are uncorrelated, it would be more appropriate to add the relative errors in quadrature.

However, given 3.8-10: No, there should not be a factor of 2. What is given in 3.9 is ##\delta q##, not ##\delta q/q##. The factor of 2 from ##\delta q## cancels the factor of 2 from ##q##.

Edit: To expand on that, 3.9 states ##\delta q = |B| \delta x## and by definition ##|q| = |B| |x|## and therefore
$$
\frac{\delta q}{|q|} = \frac{|B|\delta x}{|B| |x|} = \frac{\delta x}{|x|}.
$$

Also, do not write ##\delta * x##, it is ##\delta x## which is the error in ##x##. The ##\delta## and the ##x## are part of the same symbol representing the error in ##x##.

Of course! Embarrassing oversight on my part. Thanks a bunch!
 

1. What is the main concept of "An Introduction to Error Analysis"?

The main concept of "An Introduction to Error Analysis" by John R Taylor is to provide a comprehensive understanding of the sources, types, and propagation of errors in scientific measurements. It also teaches techniques for minimizing and analyzing these errors.

2. How can this book help improve experimental results?

This book can help improve experimental results by providing a thorough understanding of the various types of errors and how to account for them in measurements. It also offers strategies for reducing and analyzing these errors, leading to more accurate and reliable experimental results.

3. What are some examples of sources of error in scientific measurements?

Some examples of sources of error in scientific measurements include human error, equipment limitations, environmental factors, and mathematical approximations. These errors can occur at any stage of the experimental process and can affect the accuracy and precision of the results.

4. How does this book address the uncertainty principle in scientific measurements?

This book addresses the uncertainty principle by explaining how uncertainty is inherent in all measurements and how it can be quantified and minimized. It also discusses the concept of significant figures and how to properly express and propagate uncertainties in calculations.

5. Is this book suitable for all levels of scientific knowledge?

Yes, this book is suitable for all levels of scientific knowledge. It starts with the basics of error analysis and progresses to more advanced topics, making it accessible to both beginners and experienced scientists. It also includes real-world examples and practice problems to aid in understanding and application.

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