Combining Results and Errors - A Forum Saviour!

In summary, The conversation is about completing a report and needing to combine multiple sets of results for the same experiment. The formula for this involves taking the sum of the squares of the values over the squares of their errors, and then dividing by the square of their error. The resulting error is calculated by taking the sum of the inverse squares of the individual errors. The poster also expresses gratitude for the helpfulness of the forum.
  • #1
fasterthanjoao
731
1
the following post probably isn't going to be so cohesive, bear with me anyway: I'm completing a report and need to combine several sets of results for the same experiment and combine their errors to give a best value - can't for the life of me remember the formulae, i know roughly what it is - sum of the squares of the values over the squares of their error, all over the square of their error...

anyway, thanks as usual! :biggrin:

Posting/reading on this forum should become compulsory for all undergrads, its helpful.
 
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  • #2
For values y_i with errors d_i:
<y>=Sum[y_i/d_i^2]/Sum[1/d_i^2].
The resulting error is 1/D^2=Sum[1/d_i^2].
 
  • #3


Hello there,

I completely understand your struggle with remembering the formulae for combining results and errors. I can assure you that this is a common issue and there are ways to overcome it.

Firstly, it is important to have a good understanding of the underlying principles behind combining results and errors. This will not only help you remember the formulae, but also allow you to critically evaluate your results and identify any potential errors.

In terms of the formulae, you are on the right track with the sum of the squares of the values over the squares of their error. This is known as the weighted mean, where the weight is the inverse of the square of the error. It is a good idea to write down the formula and practice using it with different sets of results and errors.

Additionally, there are other methods for combining results and errors, such as using the standard deviation or standard error. These methods may be more suitable depending on the type of data you are working with. It is important to understand the differences between these methods and when to use each one.

I am glad to hear that you find this forum helpful. As scientists, it is important for us to share our knowledge and experiences with others. I would also encourage you to seek help from your peers and professors if you are still struggling with combining results and errors. Working together and discussing different approaches can greatly improve our understanding and problem-solving skills.

Best of luck with your report and I hope this helps you in your future experiments as well. Keep up the great work!
 

1. What is the importance of combining results and errors in scientific research?

Combining results and errors is crucial for obtaining accurate and reliable data. In scientific research, it is expected that there will be some degree of measurement error. By combining results and errors, researchers can determine the level of confidence in their findings and make more informed conclusions.

2. How do you calculate the combined standard error?

The combined standard error is calculated by taking the square root of the sum of the squared standard errors. This accounts for both random and systematic errors in the data. It is important to note that this calculation assumes that the errors are independent and normally distributed.

3. Can combining results and errors improve the precision of a measurement?

Yes, combining results and errors can improve the precision of a measurement. By calculating the combined standard error, researchers can reduce the uncertainty associated with their data and obtain a more precise measurement. This can increase the reliability of their findings and provide more accurate conclusions.

4. Are there any limitations to combining results and errors?

There are some limitations to combining results and errors. This method assumes that the errors are independent and normally distributed, which may not always be the case. Additionally, combining results and errors cannot account for errors that are not measured or known.

5. How can combining results and errors be applied in real-world scenarios?

Combining results and errors can be applied in various real-world scenarios, such as in medical research, environmental studies, and engineering projects. It is particularly useful when dealing with complex data sets and can help researchers make more accurate predictions and decisions based on their findings.

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