Exponential distribution problem

In summary, the Exponential Distribution Problem is a statistical problem used in various fields to find the probability of an event occurring within a specific time frame. It differs from other distributions by modeling the time between events rather than the number of events. It is characterized by a single parameter, lambda (λ), and is commonly used in reliability analysis, insurance, finance, and biology. To calculate probabilities, the value of lambda (λ) and the time frame must be known, and formulas such as P(X ≤ t) = 1 - e^(-λt) or P(X > t) = e^(-λt) can be used.
  • #1
toothpaste666
516
20

Homework Statement


The amount of time that a surveillance camera will run without having to be reset is a random variable having the exponential distribution with beta = 50 days. find the probabilities that such a camera will
a) have to be reset in less than 20 days
b) not have to be reset in at least 60 days

The Attempt at a Solution


first we integrate the function
f(x) = (1/beta)e^(-x/beta) = (1/50)e^(-x/50)
after integrating we get
-e^(-x/50) evaluated from a to b
for part a)
we are evaluating from 0 to 20 so we get
-(e^(-20/50) - 1) = 1 - e^(-20/50) = .3297

for part b) we evaluate from 60 to ∞
-(0 - e^(-60/50)) = e^(-60/50) = .3012

is this method correct?
 
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  • #2
It looks right to me.
 
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Likes toothpaste666
  • #3
It looks OK to me as well.
Another way to do part b is this: ##Pr(x \ge 60) = 1 - Pr(0 \le x < 60)##
So ##\frac 1 {50}\int_{60} ^{\infty} e^{-x/50}dx = \frac 1 {50}\left(1 - \int_0^{60}e^{-x/50}dx\right)##
 
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  • #4
ok great thank you!
 
  • #5
toothpaste666 said:

Homework Statement


The amount of time that a surveillance camera will run without having to be reset is a random variable having the exponential distribution with beta = 50 days. find the probabilities that such a camera will
a) have to be reset in less than 20 days
b) not have to be reset in at least 60 days

The Attempt at a Solution


first we integrate the function
f(x) = (1/beta)e^(-x/beta) = (1/50)e^(-x/50)
after integrating we get
-e^(-x/50) evaluated from a to b
for part a)
we are evaluating from 0 to 20 so we get
-(e^(-20/50) - 1) = 1 - e^(-20/50) = .3297

for part b) we evaluate from 60 to ∞
-(0 - e^(-60/50)) = e^(-60/50) = .3012

is this method correct?

Yes.

Here are a small number of handy facts about the exponential distribution---worth committing to memory (and pretty easy to derive for yourself).

If ##X## has distribution ##\text{Exp}(\lambda)## (so that its pdf on ##\{ x > 0 \}## is ##\lambda e^{-\lambda x}##) then:
[tex] \begin{array}{cl}
1)& EX = \displaystyle \frac{1}{\lambda} \\
2)&\text{Var} X = \displaystyle \frac{1}{\lambda^2} \\
3)& \text{Coefficient of variation} \equiv \displaystyle \frac{\text{standard deviation}}{\text{mean}} = 1 \\
4) & P(X > x) = e^{- \lambda x} , \; x \geq 0
\end{array}
[/tex]
From 4) it follows that ##P(X \leq x) = 1 - e^{- \lambda x}## for ##x \geq 0##. Also, remembering 3) is a convenient way of remembering 2).
 
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  • #6
Can anyone tell me that what happens if there is no, not used in the b part of the question?
shortly, what is the answer if the b part is: have to be reset in at least 60 days
 
  • #7
Talha said:
Can anyone tell me that what happens if there is no, not used in the b part of the question?
shortly, what is the answer if the b part is: have to be reset in at least 60 days

What do YOU think the answer should be? You have all the formulas needed to calculate the result.
 

FAQ: Exponential distribution problem

1. What is the Exponential Distribution Problem?

The Exponential Distribution Problem is a statistical problem that involves finding the probability of an event occurring within a specific time frame, given the rate at which the event occurs. It is commonly used in fields such as engineering, economics, and biology.

2. How is the Exponential Distribution different from other distributions?

The Exponential Distribution is unique in that it models the time between events occurring, rather than the number of events that occur in a given time frame. This makes it useful for predicting when the next event will occur, rather than the frequency of events.

3. What are the key characteristics of the Exponential Distribution?

The Exponential Distribution is characterized by a single parameter, lambda (λ), which represents the rate at which events occur. It has a continuous probability distribution and its shape is skewed to the right, with a long tail on the positive side.

4. How is the Exponential Distribution used in real-life applications?

The Exponential Distribution is commonly used in reliability analysis, where it can be used to model the time between equipment failures. It is also used in insurance and finance to model the time between claims or customer arrivals. In biology, it can be used to model the time between cell divisions or mutations.

5. How do you calculate probabilities using the Exponential Distribution?

To calculate probabilities using the Exponential Distribution, you need to know the value of lambda (λ) and the time frame in which the event is expected to occur. The probability of the event occurring within that time frame can then be calculated using the formula P(X ≤ t) = 1 - e^(-λt), where t is the time frame. Alternatively, the probability of the event occurring after a specific time (t) can be calculated using the formula P(X > t) = e^(-λt).

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