Solving for probability density (Griffith's 1.3)

In summary, the conversation discusses the concept of probability density and its relation to wave functions in the context of a physics problem. The question is posed about how to determine the wave function in the given scenario, and the solution is to simply assume that the probability density is constant, leading to a final conclusion that the probability density is equal to 1/pi. The conversation also touches upon the basic understanding of probability and its connection to wave functions in quantum mechanics.
  • #1
gfd43tg
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Homework Statement


Problem statement in image
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Homework Equations

The Attempt at a Solution


From my reading, I know that the probability density
[tex] \langle x \rangle = \int x |\psi|^{2} \hspace 0.05 in dx [/tex]

Where ##\psi## is the wave function and ##\langle x \rangle## is the probability density. So I figure that I will go ahead and do this,

[tex] \rho (\theta) = \int \theta |\psi|^{2} \hspace 0.05 in d \theta [/tex]

However, how do I figure out the wave function of this? I don't have a good sense for this problem and can't connect the pieces.
 

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  • #2
What you have written down is the expectation value, not the probability density. It is stated in the problem what the probability density is and what properties it should have.
 
  • #3
Okay, so then I interpret the question to mean when it says that if flicked, it is equally likely to come to rest at any angle between zero and pi

[tex] P = \int_{0}^{\pi} \rho (\theta) \hspace 0.02 in d \theta = 1 [/tex]

So if I assume ##\rho (\theta)## is constant, then ##\rho (\theta) = \frac {1}{\pi}##
 
  • #4
Correct. It does not have to be harder than that :)
 
  • #5
Maylis said:
Okay, so then I interpret the question to mean when it says that if flicked, it is equally likely to come to rest at any angle between zero and pi

[tex] P = \int_{0}^{\pi} \rho (\theta) \hspace 0.02 in d \theta = 1 [/tex]

So if I assume ##\rho (\theta)## is constant, then ##\rho (\theta) = \frac {1}{\pi}##

No assumption needed; that is exactly what is meant by "equally likely".

You seem to have some basic misunderstandings of probability. It usually has nothing to do with Quantum Mechanics or wave functions and the like. If we talk about probabilities in coin-tossing, there are no wave functions involved. If we talk about outcomes when spinning a roulette wheel, no wave functions are involved. When we talk about probabilities of car accidents, no wave functions are involved. When I want to know how long I have to wait for a bus, no wave functions come into the issue. Only when we talk about probabilities of events at the atomic or subatomic scale do wave functions enter into the calculation.
 

FAQ: Solving for probability density (Griffith's 1.3)

What is probability density?

Probability density is a measure of the likelihood of a continuous random variable taking on a specific value. It is represented as a function that assigns a probability to each possible value of the random variable.

How is probability density different from probability?

Probability density is used for continuous random variables, while probability is used for discrete random variables. Probability density is a function that assigns probabilities to a range of values, while probability is the likelihood of a specific event occurring.

What is Griffith's 1.3?

Griffith's 1.3 is a mathematical equation that describes the probability density function for a continuous random variable. It is often used in statistics and probability theory to calculate the likelihood of a particular outcome.

What is the purpose of solving for probability density?

Solving for probability density allows us to understand the distribution of a continuous random variable and make predictions about the likelihood of different outcomes. It is a fundamental concept in statistics and is used in many fields, including finance, physics, and engineering.

How do you solve for probability density using Griffith's 1.3?

To solve for probability density using Griffith's 1.3, you need to plug in the values of the random variable, mean, and standard deviation into the equation. This will give you the probability density at a specific point. You can also integrate the equation to find the probability density within a range of values.

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