A question related to an exponential random variable

In summary, the conversation discusses an exponential random variable representing the waiting times at a telephone in an office, as well as a random variable representing the outcomes of coin tosses by a staff member. The probability of the staff finishing their job in a given time is correctly expressed as the product of the probability of the waiting time being less than that time and the probability of the coin coming up heads.
  • #1
quacam09
16
0
Hi all,

Could you please answer my following question related to an exponential random variable? Thank you.

Let X represent the waiting times at a telephone in an office. Assume that X is an exponential random variable with parameter λ: P(X < t) = 1 - e^{-λ*t}

At each time when the telephone rings, a staff at the ofice will toss up a coin. If the coin comes up a tail, she will pick up the phone. If the coin comes up a head, she finishes her job.

Let Y represent the outcomes of each toss. Y = 0 if the coin comes up a tail; Y = 1 if the coin comes up a head. Asume that Y is a random variable. P(Y=0) = 1-p; P(Y = 1) = p where p is a constant (0<= p <= 1).

Let T be the time that she finishes her job.
Is it correct? P(T < t) = ( 1 - e^{-λ*t} ) * p
 
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  • #2
?Yes, that is correct. The probability of the staff finishing her job in time t is equal to the probability that the waiting time is less than t multiplied by the probability that the coin comes up heads (p).
 

1. What is an exponential random variable?

An exponential random variable is a continuous random variable that represents the time between events in a Poisson process. It follows an exponential distribution and is commonly used to model the waiting time for a particular event to occur.

2. How is an exponential random variable different from a normal random variable?

An exponential random variable is different from a normal random variable in terms of its distribution. While a normal random variable follows a bell-shaped curve, an exponential random variable follows a skewed right distribution. Additionally, the values of an exponential random variable are always positive, whereas a normal random variable can take on both positive and negative values.

3. What is the mean of an exponential random variable?

The mean, or expected value, of an exponential random variable is equal to 1/λ, where λ is the rate parameter of the exponential distribution. This means that on average, the time between events in a Poisson process will be 1/λ units of time.

4. Can an exponential random variable take on negative values?

No, an exponential random variable can only take on positive values. This is because it represents the time between events, which cannot be negative.

5. How is an exponential random variable used in real-world applications?

An exponential random variable is commonly used in situations where the occurrence of events follows a Poisson process. This can include modeling the time between customer arrivals in a queue, the time between equipment failures, or the time between radioactive decay events. It is also used in survival analysis to model the time until an event, such as death or failure, occurs.

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