What is the probability distribution for the random variable X in this problem?

In summary, the problem states that a professor has 17 keys, with only one of them unlocking a door. A random variable X represents the attempt at which the professor unlocks the door, with the unsuccessful key being saved aside. The goal is to find the most probable value of X, the specific attempt at which the professor unlocks the door, and the probability that he will unlock the door between (X-σ) and (X+σ). To solve this problem, the probabilities of the events {X=1}, {X=2}, etc. need to be determined. This can be done by considering the events that must occur for each specific attempt, and finding their corresponding probabilities.
  • #1
diracdelta
55
0

Homework Statement


Profesor has 17 keys, and only one unlocks the door.
Let random variable X be attempt at which profesor unlocks the door (key that doesn't work is saved by side)
Find:

a) Most probable value of variable X
b) In which attempt will profesor unlock the door
c) Probability that he will unlock the door between (X- σ) and (X + σ)

The Attempt at a Solution


a)
The most probable value is the x where p(x) is maximum.
How should i find it here? To find maximum i need some type of distribution.
b) This follows after i solve a)
c)also
 
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  • #2
diracdelta said:

Homework Statement


Profesor has 17 keys, and only one unlocks the door.
Let random variable X be attempt at which profesor unlocks the door (key that doesn't work is saved by side)
Find:

a) Most probable value of variable X
b) In which attempt will profesor unlock the door
c) Probability that he will unlock the door between (X- σ) and (X + σ)

The Attempt at a Solution


a)
The most probable value is the x where p(x) is maximum.
How should i find it here? To find maximum i need some type of distribution.
b) This follows after i solve a)
c)also

PF rules require you to show some effort at solving the problem.

You need to determine the probabilities ##P(X = 1), P(X = 2), \ldots##, etc. So, to say that the event ##\{X =1\}## occurs, what must happen when the professor selects keys? What is that event's probability? To say that the event ##\{ X = 2\}## occurs, what must happen when the professor selects keys? What would be the probability of that event?

Keep going like that.
 

Related to What is the probability distribution for the random variable X in this problem?

1. What is conditional probability?

Conditional probability is a statistical concept that measures the likelihood of an event occurring, given that another event has already occurred. It is calculated by dividing the probability of the joint occurrence of the two events by the probability of the first event.

2. How is conditional probability different from regular probability?

Regular probability refers to the likelihood of an event occurring without any prior knowledge or conditions. Conditional probability, on the other hand, takes into account a specific condition or event that has already occurred, and calculates the probability of another event occurring in relation to this condition.

3. How is conditional probability calculated?

Conditional probability is calculated by dividing the probability of the joint occurrence of the two events by the probability of the first event. This can be represented as P(A|B) = P(A∩B)/P(B), where P(A|B) is the conditional probability of event A given event B, P(A∩B) is the probability of both events A and B occurring, and P(B) is the probability of event B occurring.

4. What is the difference between independent and dependent events in conditional probability?

Independent events are events that do not affect the probability of each other occurring. This means that the conditional probability of one event given another event is the same as the regular probability of the first event. In contrast, dependent events are events that do affect the probability of each other occurring, and the conditional probability of one event given another event is different from the regular probability of the first event.

5. How is conditional probability used in real-life situations?

Conditional probability is used in various fields such as medicine, economics, and marketing. For example, in medicine, conditional probability can be used to determine the probability of a patient having a certain disease given their symptoms. In economics, it can be used to calculate the probability of a certain event affecting the stock market. In marketing, it can be used to predict the probability of a customer purchasing a product based on their demographic information.

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