Need help simplifying standard error formula for redshift

In summary, the standard error formula for redshift can be simplified by focusing on the key components that determine uncertainty in measurements. This involves understanding the propagation of errors from individual measurements and applying statistical methods to calculate the overall uncertainty. By streamlining the formula, one can more easily interpret the implications of redshift data in astrophysical contexts.
  • #1
Rageuke
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TL;DR Summary
Filled in all the equations for standard error in redshift (standard error formula, standard deviation formula, mean formula), would like to simplify it, too complicated otherwise thanks in advance :)
Schermafbeelding 2024-04-27 123159.png

SE = standard error, expressed as sigma(x)
n = number of observations we take into account (from a total population) when calculating the standard error
sigma-index-x = standard deviation
N = total population
x-index-i = element of that population
mu = mean of the population
-> filled in all the equations and replaced x by z (redshift) to determine the standard error in z (sigma(z))
-> as you can see, last equation is way too complicated, can anyone help me simplify it?
PS. In the finale expression, x-index-i should be substituted with z-index-i
 
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  • #2
Where you substituted your third expression into your second, why did you introduce a square root?
 
  • #3
Small mistake of mine, I corrected it, thank you for your sharp eye!
 
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  • #4
Right. And what's left is a textbook formula for standard deviation, although you are using the biased formula. Whether that matters or not depends on the size of your ##N##.
 
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FAQ: Need help simplifying standard error formula for redshift

What is the standard error formula for redshift?

The standard error formula for redshift typically involves the measurement of redshift (z) and its associated uncertainties. It can be expressed as SE(z) = σ(z) / √N, where σ(z) is the standard deviation of the redshift measurements and N is the number of measurements. This formula helps estimate the uncertainty in the calculated redshift value.

How do I calculate the standard deviation of redshift measurements?

To calculate the standard deviation of redshift measurements, first compute the mean redshift (z̄) from your dataset. Then, use the formula: σ(z) = √(Σ(z_i - z̄)² / (N - 1)), where z_i represents each individual measurement, z̄ is the mean, and N is the number of measurements. This gives you a measure of the spread of your redshift data.

What factors affect the standard error of redshift?

The standard error of redshift is affected by the number of measurements (N) and the variability of those measurements (σ(z)). A larger sample size generally leads to a smaller standard error, while greater variability in individual redshift measurements increases the standard error.

Can I simplify the standard error formula for redshift further?

Yes, if you have a consistent set of measurements, you can simplify the standard error formula by using the average standard deviation (σ) from your dataset. The formula can then be expressed as SE(z) = σ / √N, allowing for quicker calculations when you have a fixed σ across multiple datasets.

How can I interpret the standard error of redshift?

The standard error of redshift provides an estimate of the uncertainty in your redshift measurement. A smaller standard error indicates that your redshift value is more reliable and closer to the true value, while a larger standard error suggests greater uncertainty and variability in your measurements.

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