Integral of Probability Distribution Function

In summary, the probability distribution function P(r) is defined as B if the distance of someone from the center of the cable station is shorter than the radius of the station, and 0 if it is longer. B is a normalization factor chosen so that the probability of finding a r in the circle is 1. To determine B, we integrate P(r) from 0 to ∞ over r and from 0 to 2pi over θ. The function representing the cost of a cable user, C(r), is equal to λr, where λ is a constant and r is the length from the person to the cable station. The average cost for each cable station, represented by C, can be derived
  • #1
name14
2
0
The distance of someone from the center (cable station) of a circle is depicted as r, and the regular radius of that circle(the cable station) is depicted as rc. The Circle represents the entire area the cable station provides cable service for.

Given:
Probability Distribution Function

P(r) = B if r <= rc (the person’s length is shorter than the radius of the cable station so they are in the circle)

P(r) = 0 if r > rc (the person’s length is longer than the radius of the cable station so they are outside the circle, hence distribution factor is 0)

B is a "normalization factor". B is chosen so that probability of finding a r in the circle is 1. For simplicity we have written P as a function of and not both r and θ. We must remember to perform all necessary integration over both r and θ.

We determine B by integrating P(r) from 0 to ∞ (over r) and from 0 to 2pi (over θ).

1 =∫P(r)rdrdθ (I could not figure out how to put zeros under the integral symbols)

Using equations shown above for probability and integration find an expression for B. Also what assumption can I make about the location of someone within that circle.
The function representing the cost of the person who is a cable user:
C(r) =λr where λ is a constant where r is the length from the person to the cable station.

and also C =∫C(r)P(r)rdrdθ (sorry did not know how to put 0 on the bottom of integrals)

I have to derive an expression for C which represent the average cost for each cable station. Any Idea what C would be then? Thanks.

I was told to use ideas of integration and polar coordinates if I like to find the expressions.
 
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  • #2
name14 said:
The distance of someone from the center (cable station) of a circle is depicted as r, and the regular radius of that circle(the cable station) is depicted as rc. The Circle represents the entire area the cable station provides cable service for.

Given:
Probability Distribution Function

P(r) = B if r <= rc (the person’s length is shorter than the radius of the cable station so they are in the circle)

P(r) = 0 if r > rc (the person’s length is longer than the radius of the cable station so they are outside the circle, hence distribution factor is 0)

B is a "normalization factor". B is chosen so that probability of finding a r in the circle is 1. For simplicity we have written P as a function of and not both r and θ. We must remember to perform all necessary integration over both r and θ.

We determine B by integrating P(r) from 0 to ∞ (over r) and from 0 to 2pi (over θ).

1 =∫P(r)rdrdθ (I could not figure out how to put zeros under the integral symbols)

Using equations shown above for probability and integration find an expression for B. Also what assumption can I make about the location of someone within that circle.
The function representing the cost of the person who is a cable user:
C(r) =λr where λ is a constant where r is the length from the person to the cable station.

and also C =∫C(r)P(r)rdrdθ (sorry did not know how to put 0 on the bottom of integrals)

I have to derive an expression for C which represent the average cost for each cable station. Any Idea what C would be then? Thanks.

I was told to use ideas of integration and polar coordinates if I like to find the expressions.

Is that the question exactly as asked?

If yes, is there context that you have not mentioned?

CB
 
  • #3
name14 said:
The distance of someone from the center (cable station) of a circle is depicted as r, and the regular radius of that circle(the cable station) is depicted as rc. The Circle represents the entire area the cable station provides cable service for.

Given:
Probability Distribution Function

P(r) = B if r <= rc (the person’s length is shorter than the radius of the cable station so they are in the circle)

P(r) = 0 if r > rc (the person’s length is longer than the radius of the cable station so they are outside the circle, hence distribution factor is 0)

B is a "normalization factor". B is chosen so that probability of finding a r in the circle is 1. For simplicity we have written P as a function of and not both r and θ. We must remember to perform all necessary integration over both r and θ.

We determine B by integrating P(r) from 0 to ∞ (over r) and from 0 to 2pi (over θ).

1 =∫P(r)rdrdθ (I could not figure out how to put zeros under the integral symbols)

Using equations shown above for probability and integration find an expression for B. Also what assumption can I make about the location of someone within that circle.
The function representing the cost of the person who is a cable user:
C(r) =λr where λ is a constant where r is the length from the person to the cable station.

and also C =∫C(r)P(r)rdrdθ (sorry did not know how to put 0 on the bottom of integrals)

I have to derive an expression for C which represent the average cost for each cable station. Any Idea what C would be then? Thanks.

I was told to use ideas of integration and polar coordinates if I like to find the expressions.

Hi name14, :)

For the first integration,

\[1=\int_{0}^{2\pi}\int_{0}^{\infty}P(r)r\,dr\,d \theta\]

Since,

\[P(r) = \begin{cases} B & \mbox{if } r \leq r_c \\ 0 & \mbox{if } r > r_c \end{cases}\]

we have,

\[1=\int_{0}^{2\pi}\int_{0}^{\infty}P(r)r\,dr\,d \theta=\int_{0}^{2\pi}\int_{0}^{r_c}Br\,dr\,d \theta\]

\[\Rightarrow 1=B\int_{0}^{2\pi}\frac{r_{c}^{2}}{2}\,d \theta\]

\[\Rightarrow 1=B\pi r_{c}^{2}\]

\[\therefore B=\frac{1}{\pi r_{c}^{2}}\]

For the second integral,

\begin{eqnarray}

C&=&\int_{0}^{2\pi}\int_{0}^{\infty}C(r)P(r)r\,dr \,d \theta\\

&=&\lambda\int_{0}^{2\pi}\int_{0}^{\infty}P(r)r^2 \,dr\,d \theta\\

&=&B\lambda\int_{0}^{2\pi}\int_{0}^{r_c}r^2 \,dr\,d \theta\\

&=&\frac{\lambda}{\pi r_{c}^{2}}\int_{0}^{2\pi}\int_{0}^{r_c}r^2 \,dr\,d \theta\\

&=&\frac{\lambda}{\pi r_{c}^{2}}\left(\frac{2\pi r_{c}^{3}}{3}\right)\\

&=&\frac{2\lambda r_{c}}{3}\\

\end{eqnarray}

Kind Regards,
Sudharaka.
 

FAQ: Integral of Probability Distribution Function

What is the Integral of a Probability Distribution Function?

The integral of a probability distribution function is a mathematical operation that calculates the total area under the curve of the probability distribution function. It is used to determine the likelihood of a random variable falling within a certain range of values.

Why is the Integral of a Probability Distribution Function important?

The integral of a probability distribution function is important because it allows us to calculate the probability of events occurring within a certain range, which is essential in many fields such as statistics, economics, and engineering. It also helps us understand the behavior and characteristics of a random variable.

How is the Integral of a Probability Distribution Function calculated?

The integral of a probability distribution function can be calculated using various techniques, such as the fundamental theorem of calculus, numerical integration, or using specific formulas for different types of distributions. The specific method used will depend on the complexity of the function and the available tools.

What is the relationship between the Integral of a Probability Distribution Function and the Cumulative Distribution Function?

The cumulative distribution function (CDF) is the integral of the probability distribution function (PDF) and represents the probability that a random variable will be less than or equal to a given value. In other words, the CDF is the accumulation of probabilities from the lower end of the distribution up to a certain point, while the PDF represents the probability of a specific value occurring.

How can the Integral of a Probability Distribution Function be applied in real-world situations?

The integral of a probability distribution function has various applications in real-world situations, such as risk analysis, forecasting, and decision-making. For example, it can be used to calculate the probability of a stock price falling within a certain range, or the likelihood of a natural disaster occurring in a specific area. It is also used in finance to model and analyze market trends and in quality control to assess the reliability of products.

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