What is the physical or statistical meaning of this integral

In summary, the integral \int^{a}_{o} g(\vartheta) d(\vartheta) = \int^{\infty}_{a} g(\vartheta) d(\vartheta) finds a point \vartheta = a for which the area under the curve (the Gaussian) between 0 to a and a to \infty are equal. It represents the 50% likelihood range and works for any symmetric probability distribution. The norm of the probability distribution should be 1 for this to be valid.
  • #1
jam_27
48
0
What is the physical or statistical meaning of the following integral

[tex]\int^{a}_{o} g(\vartheta) d(\vartheta)[/tex] = [tex]\int^{\infty}_{a} g(\vartheta) d(\vartheta)[/tex]

where [tex]g(\vartheta)[/tex] is a Gaussian in [tex]\vartheta[/tex] describing the transition frequency fluctuation in a gaseous system (assume two-level and inhomogeneous) .

[tex]\vartheta = \omega_{0} -\omega[/tex], where [tex]\omega_{0}[/tex] is the peak frequency and [tex]\omega[/tex] the running frequency.

I can see that the integral finds a point [tex]\vartheta = a[/tex] for which the area under the curve (the Gaussian) between 0 to a and a to [tex]\infty[/tex] are equal.

But is there a statistical meaning to this integral? Does it find something like the most-probable value [tex]\vartheta = a[/tex]? But the most probable value should be [tex]\vartheta = 0[/tex] in my understanding! So what does the point [tex]\vartheta = a[/tex] tell us?

I will be grateful if somebody can explain this and/or direct me to a reference.

Cheers

Jamy
 
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  • #2
jam_27 said:
[tex]\int^{a}_{o} g(\vartheta) d(\vartheta)[/tex] = [tex]\int^{\infty}_{a} g(\vartheta) d(\vartheta)[/tex]

But is there a statistical meaning to this integral?

Hi Jamy! :smile:

It's the 50% likelihood range …

50% likely that the result will be between ±a

(and it works for any symmetric probability distribution, not just Gaussian :wink:)
 
  • #3
tiny-tim said:
Hi Jamy! :smile:

It's the 50% likelihood range …

50% likely that the result will be between ±a

(and it works for any symmetric probability distribution, not just Gaussian :wink:)

Thanks a ton for the reply. Could you please provide a reference/book. I want to see how its 50% likely.
Cheers
Jamy:smile:
 
  • #4
Well I suppose the domain is on positive values. For it to be a probability distribution its norm should be unity.

[tex] \int^{\infty}_{o} g(\vartheta) d(\vartheta) = 1 [/tex]

The 50% follows from 11th grade math, by the rules of how to add integrals over different intervals.
 

Related to What is the physical or statistical meaning of this integral

1. What is the purpose of an integral in scientific research?

An integral is a mathematical tool used to calculate the area under a curve. In scientific research, it is often used to find the total amount or quantity of something, such as the total volume of a substance or the total energy of a system.

2. How is an integral related to the concept of differentiation?

An integral and differentiation are inverse operations of each other. Integration is used to find the area under a curve, while differentiation is used to find the slope of a curve. In other words, integration tells us the total change, while differentiation tells us the rate of change.

3. What is the difference between a definite and indefinite integral?

A definite integral has specific limits of integration, while an indefinite integral does not. This means that a definite integral will give a specific numerical value, while an indefinite integral will give a function with a constant of integration.

4. How is an integral used to solve real-world problems?

Integrals are used in many fields of science, such as physics, chemistry, and engineering, to solve real-world problems. They can be used to calculate the area, volume, or total energy of a system, as well as to model the behavior of complex systems.

5. What is the statistical meaning of an integral?

In statistics, an integral is used to calculate the probability of a certain outcome or event occurring. It can also be used to find the cumulative distribution function, which gives the probability of a random variable being less than or equal to a specific value.

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