What are some recommended textbooks for error analysis in scientific research?

In summary, some recommended textbooks for error analysis in scientific research include "Measurement Error and Research Design" by Madhu Viswanathan, "Error and Uncertainty in Scientific Practice" by Marcel Boumans, and "Measurement Errors in Surveys" by Paul P. Biemer. These texts cover topics such as sources of error, types of measurement error, and methods for minimizing and analyzing error in scientific research. They also provide case studies and practical examples to help readers understand and apply the concepts in their own research. Overall, these textbooks are valuable resources for researchers looking to improve the accuracy and reliability of their data.
  • #1
Elwin.Martin
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  • #2
Bevington is the standard book on error analysis for physics students and physicists. It's well written and relatively easy to understand. I'd definitely start there.
 
  • #4
Andy Resnick said:

Since I don't know very much about either, why this over Bevington?
That looks like same publisher as the Taylor book on Mechanics, assuming they're the same author I would think that Taylor's book should be very clearly written?

Edit:
After viewing the introductions/prefaces for both it would appear that the Taylor book is truly geared for a first viewing of the material. That's definitely a good thing, but I may need some (slightly) more advanced material after I finish. Do you have a recommendation for a reference or slightly more advanced book to follow Taylor?

Sorry for asking so many questions ^^;
 
Last edited:
  • #5
This is what was said to me:

"As far as data analysis goes, beyond the basics (mean, sigma, chi-squared fits) it would be good for you to understand maximum likelihood fits (particularly multi-dimensional ML fits). Also, we probably will want to explore using multi-variate discriminators."

Since I took AP Stat back in high school, I can't really say I've had Stats :P because that class was really poorly put together, so I'm definitely going to recover the basics.

Now, for Bevington [3rd edition] I'm looking at covering:
Chapter 1 - Uncertainties in Measurements
Chapter 2 - Probability Distributions
Chapter 3 - Error Analysis
Chapter 4 - Estimates of Means and Errors
Should I cover Chapter 5 - Chapter 9?
I'm not sure what I will need as prereq to beginning Chapter 10 on Maximum Likelihood...and I'm guessing I'll need Chapter 11 - Testing the Fit

For Taylor [2nd Edition] I'm looking at the following:
(from Part I)
Chapter 1. Prelinary Description of Error Analysis
Chapter 2. How to Report and Use Uncertainties
Chapter 3. Propagation of Uncertainties
Chapter 4. Statistical Analysis of Random Uncertainties
Chapter 5. The Normal Distribution
(from Part II)
Chapter 6. Rejection of Data
Chapter 7. Weighted Averages
Chapter 12. The Chi-Squared Test for a Distribution
I'm not sure what parts of Chapters 8 - Chapter 11 I will need.

The work I'll be doing [though I don't know exactly what yet] will be dealing with particle data, if this helps in determining what I need to know. I'm learning to work with a various packages in ROOT like RooFit and TVMA, but again I'm not sure if that helps for context much since I'm not very far into this yet!

I am not entirely sure that Bevington (I doubt Taylor has the material) has the last two things he mentioned: Multidimensional MLs and Multivariate Discriminators, so it would be great to know if they do or where I can learn this material. To be honest, I don't even know what is meant by the last term and Google did not give me an immediate answer.

Any recommendations on what to cover from where? :P I've got three whole months to work on this stuff, so I should be okay double covering a bit, right?
 
  • #6
Taylors error analysis book may not be super advanced but Taylor is a fantastic author in my opinion. Grab his book!
 
  • #7
Jorriss said:
Taylors error analysis book may not be super advanced but Taylor is a fantastic author in my opinion. Grab his book!

This is the feeling I've been getting in general, I have a copy on hand ( :!) University Libraries) and it feels sort of like his Mechanics book.

Do you have any recommendations for an advanced book to follow his?
 
  • #8
Elwin.Martin said:
Since I don't know very much about either, why this over Bevington?
That looks like same publisher as the Taylor book on Mechanics, assuming they're the same author I would think that Taylor's book should be very clearly written?

Edit:
After viewing the introductions/prefaces for both it would appear that the Taylor book is truly geared for a first viewing of the material. That's definitely a good thing, but I may need some (slightly) more advanced material after I finish. Do you have a recommendation for a reference or slightly more advanced book to follow Taylor?

Sorry for asking so many questions ^^;

I have a few texts on error analysis, for whatever reason Taylor is the easiest one for me to use- definitely check a few different ones out of your library, YMMV :)
 
  • #9
I know this isn't a popular subject, but I'd like to bump this just to see if anyone has any other input.

Someone recommended this to me as well:
http://arxiv.org/pdf/physics/9711021v2.pdf

So I'm looking at a combined approach reading through that paper, and working through bits of Bevington and Taylor together.
 

1. What is Error Analysis in textbooks?

Error analysis in textbooks is the process of identifying and quantifying the errors made by students in their written work. It involves analyzing the types of errors made and the frequency of those errors in order to understand the areas in which students need more instruction.

2. Why is Error Analysis important in textbooks?

Error analysis is important in textbooks because it allows teachers to identify and address common errors made by students. It can also help teachers adjust their teaching strategies to better meet the needs of their students.

3. How can Error Analysis be used in the classroom?

Error analysis can be used in the classroom by collecting and analyzing student work, and then using the results to inform lesson planning and instruction. Teachers can also provide targeted feedback to students based on their individual errors.

4. What are the benefits of using Error Analysis in textbooks?

Using error analysis in textbooks can help students improve their writing skills by identifying and addressing their common errors. It can also help teachers tailor their instruction to meet the specific needs of their students.

5. Are there any limitations to Error Analysis in textbooks?

While error analysis can be a useful tool, it does have some limitations. It may not always account for the context or complexity of a student's writing, and it may not be feasible to analyze every single error made by students. Additionally, error analysis should not be the only method used to evaluate student writing and should be used in conjunction with other assessments.

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