Asymmetric uncertainty intervals in astrophysical data

In summary: What is your goal? Your goal is to find an average value of the observed quantity, and calculate a percent uncertainty. But the authors have already given you that.
  • #1
ElectroFractal
11
0
Homework Statement
I have come across astrophysical data where the data have asymmetrical uncertainty intervals like this for example: 4.467[SUP]+0.064[/SUP][SUB]-0.096[/SUB]. I cannot realize how to calculate an average of this quantity, and a percent uncertainty.
Relevant Equations
I calculated the upper and lower value: 4.467+0.064=4.531 and 4.467-0.096=4.371, and found the average which is 4.451, and it's different from the value 4.467.
My initial guess was to calculate the upper and lower value, and then average those two values, but I don't know whether this is correct to make the uncertainty interval symmetric.

After I calculated the average value, I subtracted it form the upper and lower value, and obtained the symmetric interval: 4.451+-0.08. Thus, the percent uncertainty is:
0.08/4.451 = 1.79%

My question is if this way of thinking is a correct one, and if there are other techniques to obtain my goal?
 
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  • #2
ElectroFractal said:
is a correct one
Obviously: No. Otherwise the authors would have published their result in that manner.

What is the motivation behind your 'goal' ?
 
  • #3
My motivation is to find an average value of the observed quantity, and calculate a percent uncertainty. I am doing an ML project related to astronomical observations, and I am trying to do feature engineering to obtain better results from the model.
 
  • #4
ElectroFractal said:
My motivation is to find an average value of the observed quantity, and calculate a percent uncertainty.

But the authors clearly did not think this was the correct way to express the uncertainty, otherwise they would have done it the other way.
 
  • #5
So, is there a way to calculate what I want, or I should forget about this, and try to do something different?
 
  • #6
You want the error to be symmetric. The authors didn't think it was. You need to decide how to handle this disagreement.
 
  • #7
As @Vanadium 50 said, you need to think about what you are trying to do. What do you mean by the "average"? An average usually refers to reducing a list of values to a single number by adding up the values and dividing by the number of values. But here you have just a single value, so using the term average doesn't really make sense. Do you mean the most likely value? The authors have given you that. It is the 4.467 value.
 
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Related to Asymmetric uncertainty intervals in astrophysical data

1. What are asymmetric uncertainty intervals in astrophysical data?

Asymmetric uncertainty intervals in astrophysical data refer to the range of possible values for a measurement or observation, where the upper and lower bounds of the range are not equal. This means that the uncertainty or error in the measurement is not symmetrical, and there is a greater likelihood of the true value falling within a certain range of values.

2. How are asymmetric uncertainty intervals calculated?

Asymmetric uncertainty intervals are typically calculated using statistical methods, such as Bayesian analysis or Monte Carlo simulations. These methods take into account the known uncertainties in the data and provide a range of possible values for the measurement, rather than a single value.

3. What causes asymmetric uncertainty intervals in astrophysical data?

Asymmetric uncertainty intervals can be caused by a variety of factors, including measurement errors, instrumental limitations, and inherent variations in the data. In astrophysics, sources of uncertainty can also include the effects of gravitational lensing, redshift, and other cosmological phenomena.

4. How do asymmetric uncertainty intervals impact scientific conclusions?

Asymmetric uncertainty intervals are important to consider when interpreting scientific results, as they can affect the accuracy and precision of conclusions drawn from the data. They can also provide valuable insights into the underlying uncertainties and limitations of the data, allowing for a more nuanced understanding of the results.

5. How can scientists account for asymmetric uncertainty intervals in their analyses?

Scientists can account for asymmetric uncertainty intervals by using appropriate statistical methods, such as Bayesian analysis, to calculate and incorporate the uncertainties into their analyses. They can also use visual aids, such as error bars or confidence intervals, to clearly communicate the range of possible values for a measurement or observation.

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