Independent Trials: Probability of Events A_i

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In summary, the probability of event A_i, which represents not choosing the ball numbered i in n selections from an urn with N balls, is (N-1)/N)^n. The probability of both A_i and A_j occurring is ((N-2)/N)^n. However, these events are not independent. If they were, the probability of no colors being chosen would be (N-1)^nN, which is not equal to 0. This suggests that failing to draw one color increases the chances of drawing the others.
  • #1
IniquiTrance
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Say I have an urn containing a set of balls numbered 1 through N. I then make n selections from the urn with replacement. Thus each selection is independent.

Let the event: [tex]A_{i}[/tex]
[tex]i=1,2,3...,N[/tex]

be that the ball numbered i was not chosen in the n selections.

Then:

[tex]P(\mathbf{A_{i}})=\left(\frac{N-1}{N}\right)^{n}[/tex]

and [tex]P(\mathbf{A_{i}A_{j}})=\left(\frac{N-2}{N}\right)^n}[/tex] and so on...

But aren't the events [tex]A_{i}[/tex] [tex]i=1,2,3...,N[/tex] independent as well?

So shouldn't the probability of
[tex]P(\mathbf{A_{i}A_{j}})=P(\mathbf{A_{i}})P(\mathbf{A_{j}})=\left(\frac{N-1}{N}\right)^{2n}=\left(\frac{2(N-1)}{N}\right)^{n}[/tex]
 
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  • #2
You have just proved that the events [itex]A_i[/itex] and [itex]A_j[/itex] are not independent.

If they were then the probability of no colours being chosen would be

[tex](\frac{N-1}{N})^{nN}[/itex]

but this exprssion is obviously not 0.

(Intuitively failing to draw one colour increases the chances of drawing each of the others.)
 
  • #3
Martin Rattigan said:
You have just proved that the events [itex]A_i[/itex] and [itex]A_j[/itex] are not independent.

If they were then the probability of no colours being chosen would be

[tex](\frac{N-1}{N})^{nN}[/itex]

but this exprssion is obviously not 0.

(Intuitively failing to draw one colour increases the chances of drawing each of the others.)

Ah ok. Thanks!
 

Related to Independent Trials: Probability of Events A_i

What is the concept of independent trials?

The concept of independent trials refers to a series of repeated experiments or events where the outcome of one trial does not affect the outcome of the next trial. This means that each trial has the same probability of occurring regardless of the outcome of previous trials.

How is the probability of independent events calculated?

The probability of independent events is calculated by multiplying the individual probabilities of each event. For example, if event A has a probability of 0.5 and event B has a probability of 0.3, the probability of both events occurring together is 0.5 x 0.3 = 0.15.

What is the formula for calculating the probability of multiple independent trials?

The formula for calculating the probability of multiple independent trials is P(A or B) = P(A) + P(B) - P(A and B), where P(A) and P(B) are the individual probabilities of each event and P(A and B) is the probability of both events occurring together.

How does the number of trials affect the overall probability?

The more independent trials that are conducted, the closer the observed probability will be to the expected theoretical probability. This means that as the number of trials increases, the accuracy of the probability calculation also increases.

What real-life situations involve independent trials and probability calculations?

Independent trials and probability calculations are commonly used in fields such as statistics, economics, and gambling. For example, in gambling, the probability of winning a game of roulette is calculated by considering the independent trials of each spin of the wheel.

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