Dartboards and Normal Distribution: Probability of Hitting

In summary: The nature of a probability density is that f(\mathbf{x}) \geq 0 for all \mathbf{x} \in \mathbb{R}^2 and f(x) = 1.
  • #1
Lemniscates
9
0
I was reading this problem on calculating the probability of hitting a certain region on a dartboard. The number of hits the dart thrower will land at a certain radius R on the dartboard is proportional to e^(-R^2). The task is to take a certain portion of a ring (or annulus) on the dartboard and calculate the probability of hitting it. The full problem statement is at this link, if you could read the first two pages to see the parts relevant to my question, that would be nice: http://ocw.mit.edu/courses/mathematics/18-01sc-single-variable-calculus-fall-2010/unit-3-the-definite-integral-and-its-applications/part-c-average-value-probability-and-numerical-integration/session-62-integrals-and-probability/MIT18_01SCF10_Ses62d.pdf

My question is: why is the probability a ratio of volumes and not areas? The pdf only partially addresses it. Given that the height of the graph ce^(r^2) is the number of hits, my intuitive feeling is that the area under the curve is the number of hits for that range of radii. Could someone explain why it's a volume?
 
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  • #2
By the way, should I be asking this in homework help? I felt my question was mostly related to the concept of integration and not the specific question, so I posted it here.
 
  • #3
Lemniscates said:
I was reading this problem on calculating the probability of hitting a certain region on a dartboard. The number of hits the dart thrower will land at a certain radius R on the dartboard is proportional to e^(-R^2). The task is to take a certain portion of a ring (or annulus) on the dartboard and calculate the probability of hitting it.

My question is: why is the probability a ratio of volumes and not areas? The pdf only partially addresses it. Given that the height of the graph ce^(r^2) is the number of hits, my intuitive feeling is that the area under the curve is the number of hits for that range of radii. Could someone explain why it's a volume?

What you have is a random variable [itex]X[/itex] (the point where a dart hits) which takes values on the plane [itex]\mathbb{R}^2[/itex], with an associated probability density function [itex]f : \mathbb{R}^2 \to \mathbb{R}[/itex].

When you calculate the probability that [itex]X \in A \subset \mathbb{R}^2[/itex], what you are by definition calculating is the double integral
[tex]
P(X \in A) = \iint_A f(\mathbf{x})\,\mathrm{d}A.
[/tex]
The nature of a probability density is that [itex]f(\mathbf{x}) \geq 0[/itex] for all [itex]\mathbf{x} \in \mathbb{R}^2[/itex] and
[tex]
P(X \in \mathbb{R}^2) = \iint_{\mathbb{R}^2} f(\mathbf{x})\,\mathrm{d}A = 1.
[/tex]
Those integrals look like an area times a "height", making them "volumes".
 
  • #4
A lot of that notation is new to me, but I've done a little bit of Googling to make some sense out of it.

I'm still confused. What is the probability density function in this case? It wouldn't be c*e^(-r^2) would it? Because to me that seems like a function that takes a real number and puts out a real number, while the definition of the probability function you listed seems to to suggest that the function takes a two dimensional value and puts out a real number.

What is the reasoning behind the probability of X being within A (which I take it is what you're calling the area of the dartboard?) being defined as a double integral?
 
  • #5
A function such as f(x,y) = x^2 only employs the variable x to compute a result, but it is still a function of two variables, just by the way it is defined. So the fact that a function only employs R to determine a result doesn't mean it is a function of 1 variable. How many variables are involved depends on how the article defines the function. It may be that the variable R is not involved at all! For example if the density function is defined a function of f(x,y), it may be that you are expected to find R from x and y as an intermediate step.
 

1. How does the normal distribution affect the probability of hitting a dartboard?

The normal distribution, also known as the Gaussian distribution, is a mathematical concept that describes the probability of a variable falling within a certain range of values. In the case of a dartboard, the normal distribution can be used to calculate the probability of hitting a specific area on the board based on factors such as the skill of the player, distance from the board, and the size of the target area.

2. What is the relationship between standard deviation and the probability of hitting a dartboard?

The standard deviation is a measure of how spread out a set of data is from its mean. In the context of dartboard hitting probability, a smaller standard deviation indicates a higher likelihood of hitting the target area, as the data points are closer to the mean and there is less variability in the throws.

3. Can the normal distribution be used to predict the probability of hitting a bullseye on a dartboard?

Yes, the normal distribution can be used to predict the probability of hitting a bullseye on a dartboard. By inputting the relevant variables such as distance and skill level into the normal distribution formula, the probability of hitting the bullseye can be calculated.

4. How does the shape of the normal distribution curve affect the probability of hitting a dartboard?

The shape of the normal distribution curve can affect the probability of hitting a dartboard by indicating the likelihood of hitting different areas on the board. For example, a taller and narrower curve indicates a higher probability of hitting a specific target area, while a flatter and wider curve indicates a lower probability.

5. Are there any other factors besides normal distribution that can affect the probability of hitting a dartboard?

Yes, there are other factors that can affect the probability of hitting a dartboard, such as wind, lighting, and the quality of the dartboard itself. These factors may not be accounted for in the normal distribution calculation and can impact the accuracy of the predicted probability.

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