Uniform Probability over Real Line?

In summary, the conversation discusses a two-ended laser spinner and the probability density of the point at which the laser will land on a wall a meter away. The angle at which the laser lands is uniformly distributed over a range of -π/2 to π/2. By setting up a right triangle and using the law of sines, the probability density of the point Y is found to be a uniform distribution over the entire real number line. However, by making a transformation and assuming a uniform distribution for X, the final probability density of Y is determined to be 1/{\pi}(1+y^2).
  • #1
gajohnson
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Homework Statement



Consider a two-ended laser spinner; that is a pen-like laser acting as the arrow mounted on a pin at the center of a spinner. Suppose the center of the disk is one meter away from a wall of infinite extent marked with a linear scale, with zero at the point closest the center of the spinner and negative numbers to left, positive to the right.

The laser is spun and comes to a rest projecting for one of its ends at a point Y on the
scale (with probability zero the laser will stop parallel to the wall and miss it; we ignore
that possibility). Suppose that the angle X the laser makes to the perpendicular to the
wall is uniformly distributed over –π/2 to π/2. Find the probability density of Y.

Homework Equations


The Attempt at a Solution



The angle at which the laser lands must have PDF [itex]f_X(x)=1/{\pi}[/itex]

That is, it is the uniform distribution over pi radians.

Next, I set up a right triangle and find that the angle opposite the the 1 meter side is equal to [itex]{\pi}/2-X[/itex] and that the angle opposite the base (call it B) is simply X (given by the PDF above). Using the law of sines (and that the distance from the "infinite wall" to the spinner is 1 meter) to find:

[itex]B=sinx/sin({\pi}/2-X)[/itex]

It seems clear to me that Y is then the uniform distribution over [itex]lim B [/itex] as [itex] x->{\pi}/2 + - (lim B [/itex] as [itex] x->-{\pi}/2)[/itex]

This is the entire real number line and so the PDF of Y does not exist.

Is this right (even if my steps are less than rigorous)? Any help would be appreciated.
 
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  • #2
Let the origin of the Y axis along the wall be the foot of the 1 meter perpendicular side. Then for a point Y on that axis you have ##\frac Y 1 =\tan X##. Try starting with that.
 
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  • #3
So much simpler! My trig is too rusty.

Ok, so then I find that g(Y)=arctan(Y) and, after taking the derivative, I make the transformation assuming the uniform distribution described before for X.

I get [itex]f_Y(y)=1/{\pi}(1+y^2)[/itex]

Is it that simple? Thanks!
 
Last edited:
  • #4
gajohnson said:
So much simpler! My trig is too rusty.

Ok, so then I find that g(Y)=arctan(Y) and, after taking the derivative, I make the transformation assuming the uniform distribution described before for X.

I get [itex]f_Y(y)=1/{\pi}(1+y^2)[/itex]

Is it that simple? Thanks!

Confirmed this elsewhere. It is indeed that simple. Appreciate your help!
 
  • #5
gajohnson said:
Confirmed this elsewhere. It is indeed that simple. Appreciate your help!

Yes, it is. Sorry I couldn't get back to you yesterday. Too busy.
 

1. What is a uniform probability over real line?

A uniform probability over real line is a continuous probability distribution where every outcome within a given range has an equal chance of occurring. This means that the probability of any specific outcome is the same as any other outcome within the range.

2. What is the formula for calculating the probability of a specific outcome in a uniform probability distribution?

The formula for calculating the probability of a specific outcome in a uniform probability distribution is p(x) = 1/(b-a), where b is the upper bound and a is the lower bound of the range.

3. How is a uniform probability over real line different from other types of probability distributions?

A uniform probability over real line is different from other types of probability distributions, such as normal or exponential distributions, because it assumes that all outcomes within a given range are equally likely. Other distributions may have different probabilities for different outcomes.

4. What are some real-life examples of a uniform probability over real line?

Some real-life examples of a uniform probability over real line include the roll of a fair die, the selection of a random number from a set of numbers, or the flipping of a coin. In each of these cases, all possible outcomes have an equal chance of occurring.

5. How is a uniform probability over real line used in scientific research?

A uniform probability over real line is commonly used in scientific research to model random processes, such as the distribution of particles in a gas or the occurrence of mutations in genetic studies. It can also be used to generate random numbers for simulations and statistical analyses.

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