Probability of Independent Events

P(\text{at least one occurs}) = P(A_1 \cup A_2 \cup A_3)\\= p_1 + p_2 + p_2 - p_{12} - p_{13} - p_{23} + p_{123} .Is that using the fact that: P(A_1 \cup A_2 \cup A_3) = P(A_1) + P(A_2) + P(A_3) - P(A_1 \cap A_2) - P(A_1 \cap A_3) - P(A_2 \cap A_3) + P(A_1 \cap A_2 \cap A_3)
  • #1
_N3WTON_
351
3

Homework Statement


Consider three events A1, A2, and A3, and let pi = P(Ai), for i = 1, 2, 3.
a) Express the probability that at least one of these three events occurs in terms of the pi ’s.
b) Express the probability that at least two of the events occur.
c) Suppose that A1, A2 and A3 are independent events. Verify that P(A1|A2 ∩ A3) = P(A1).

Homework Equations

The Attempt at a Solution


For part c I had no trouble obtaining a solution:
P(A1|A2 ∩ A3) = P[A1 ∩ (A2 ∩ A3)] P(A2 ∩ A3)
By independence, we have P[A1 ∩ (A2 ∩ A3)] = P(A1)P(A2)P(A3) and P(A2 ∩ A3) = P(A2)P(A3), and the result follows. However, I am having some trouble with the first two. The answer given by the instructor for a is:
1 − (1 − p1)(1 − p2)(1 − p3)
and for b is:
p1p2(1 − p3) + p1(1 − p2)p3 + (1 − p1)p2p3 + p1p2p3. I am not trying to dispute these answers, I am just having trouble understanding where they come from. Specifically, I do not understand the expression (1-p1), I assume that this is the probability that either p2 or p3 occur, but I'm not sure why. I was hoping somebody could give me some sort of explanation. Thanks.
 
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  • #2
1-pi is the probability of Ai not occurring.
 
  • #3
Orodruin said:
1-pi is the probability of Ai not occurring.
Ok, thanks...so then the expression p1p2(1-p3) would be the probability that either p1 or p2 occur?
 
  • #4
It is the probability that A1 and A2 occur and that A3 does not - assuming the events are independent.
 
  • #5
Orodruin said:
It is the probability that A1 and A2 occur and that A3 does not - assuming the events are independent.
ok, thank you
 
  • #6
_N3WTON_ said:

Homework Statement


Consider three events A1, A2, and A3, and let pi = P(Ai), for i = 1, 2, 3.
a) Express the probability that at least one of these three events occurs in terms of the pi ’s.
b) Express the probability that at least two of the events occur.
c) Suppose that A1, A2 and A3 are independent events. Verify that P(A1|A2 ∩ A3) = P(A1).

Homework Equations

The Attempt at a Solution


For part c I had no trouble obtaining a solution:
P(A1|A2 ∩ A3) = P[A1 ∩ (A2 ∩ A3)] P(A2 ∩ A3)
By independence, we have P[A1 ∩ (A2 ∩ A3)] = P(A1)P(A2)P(A3) and P(A2 ∩ A3) = P(A2)P(A3), and the result follows. However, I am having some trouble with the first two. The answer given by the instructor for a is:
1 − (1 − p1)(1 − p2)(1 − p3)
and for b is:
p1p2(1 − p3) + p1(1 − p2)p3 + (1 − p1)p2p3 + p1p2p3. I am not trying to dispute these answers, I am just having trouble understanding where they come from. Specifically, I do not understand the expression (1-p1), I assume that this is the probability that either p2 or p3 occur, but I'm not sure why. I was hoping somebody could give me some sort of explanation. Thanks.

The way the problem is written, independence does not enter until part (c), so (presumably), A1, A2, A3 need not be independent in parts (a) and (b). In that case you do not have enough information to do parts (a) and (b); you would need to know also the probabilities ##P(A_1 \cap A_2)##, ##P(A_1 \cap A_3##, ##P(A_2 \cap A_3## and ##P(A_1 \cap A_2 \cap A_3)##. If you did know these, the inclusion-exclusion principle would allow you to compute P{at least one }. A less well-known extension of the inclusion-exclusion principle would allow for calculation of P{exactly 1 occurs}, P{exactly 2 occur}, P{at least 2 occur}, etc. See, eg.,
http://www.tricki.org/article/To_co...nts_occur_use_generalized_inclusion-exclusion

If the events ARE independent, the inclusion-exclusion probabilities simplify a lot, and you can obtain explicit results. Below, let ##p_{i} = P(A_i)##, ##p_{ij} = P(A_i \cap A_j)## and ##p_{123} = P(A_1 \cap A_2 \cap A_3)## (with no independence assumptions).
The instructor's answer for (a) comes from the fact that
[tex] P(\text{at least one occurs}) = P(A_1 \cup A_2 \cup A_3)\\
= p_1 + p_2 + p_2 - p_{12} - p_{13} - p_{23} + p_{123} .[/tex]
Assuming indepedence, we can go further, as we would then have
[tex] P(\text{at least one occurs})
= p_1 + p_2 + p_3 - p_1 p_2 - p_1 p_3 - p_2 p_3 + p_1 p_2 p_3 \\
= 1 - (1-p_1)(1 - p_2)(1 - p_3)
[/tex]BTW: even "pairwise independence" is not enough: it is possible to have ##p_{12} = p_1 p_2##, ##p_{13} = p_1 p_3## and ##p_{23} = p_2 p_3##, but ##p_{123} \neq p_1 p_2 p_3##.
 
  • #7
Ray Vickson said:
The way the problem is written, independence does not enter until part (c), so (presumably), A1, A2, A3 need not be independent in parts (a) and (b). In that case you do not have enough information to do parts (a) and (b); you would need to know also the probabilities ##P(A_1 \cap A_2)##, ##P(A_1 \cap A_3##, ##P(A_2 \cap A_3## and ##P(A_1 \cap A_2 \cap A_3)##. If you did know these, the inclusion-exclusion principle would allow you to compute P{at least one }. A less well-known extension of the inclusion-exclusion principle would allow for calculation of P{exactly 1 occurs}, P{exactly 2 occur}, P{at least 2 occur}, etc. See, eg.,
http://www.tricki.org/article/To_co...nts_occur_use_generalized_inclusion-exclusion

If the events ARE independent, the inclusion-exclusion probabilities simplify a lot, and you can obtain explicit results. Below, let ##p_{i} = P(A_i)##, ##p_{ij} = P(A_i \cap A_j)## and ##p_{123} = P(A_1 \cap A_2 \cap A_3)## (with no independence assumptions).
The instructor's answer for (a) comes from the fact that
[tex] P(\text{at least one occurs}) = P(A_1 \cup A_2 \cup A_3)\\
= p_1 + p_2 + p_2 - p_{12} - p_{13} - p_{23} + p_{123} .[/tex]
Assuming indepedence, we can go further, as we would then have
[tex] P(\text{at least one occurs})
= p_1 + p_2 + p_3 - p_1 p_2 - p_1 p_3 - p_2 p_3 + p_1 p_2 p_3 \\
= 1 - (1-p_1)(1 - p_2)(1 - p_3)
[/tex]BTW: even "pairwise independence" is not enough: it is possible to have ##p_{12} = p_1 p_2##, ##p_{13} = p_1 p_3## and ##p_{23} = p_2 p_3##, but ##p_{123} \neq p_1 p_2 p_3##.
Just to be clear, you simplification assuming independence comes from the fact that:
[itex] P(A_{i1} \cap A_{i2} \cap ... \cap A_{ik}) = P(A_{i1}) * P(A_{i2}) *...*P(A_{ik}) [/itex] ?
 
  • #8
_N3WTON_ said:
Just to be clear, you simplification assuming independence comes from the fact that:
[itex] P(A_{i1} \cap A_{i2} \cap ... \cap A_{ik}) = P(A_{i1}) * P(A_{i2}) *...*P(A_{ik}) [/itex] ?

Yes.
 
  • #9
Ray Vickson said:
Yes.
Ok fantastic, thank you for the explanation!
 

What is probability of independent events?

Probability of independent events refers to the likelihood of two or more events occurring at the same time, where the outcome of one event does not affect the outcome of the other.

How do you calculate probability of independent events?

To calculate probability of independent events, you multiply the probabilities of each event occurring individually. For example, if event A has a probability of 0.5 and event B has a probability of 0.6, the probability of both events occurring is 0.5 x 0.6 = 0.3.

What is the difference between independent and dependent events?

Independent events are events where the outcome of one event does not affect the outcome of the other. Dependent events, on the other hand, are events where the outcome of one event does affect the outcome of the other.

How can you identify if events are independent or dependent?

You can identify if events are independent or dependent by determining if the outcome of one event affects the outcome of the other. If the events are unrelated and do not influence each other, they are independent. If the events are related and the outcome of one event affects the outcome of the other, they are dependent.

What is the significance of probability of independent events in real life?

Probability of independent events is used in various fields, such as finance, sports, and weather forecasting, to predict the likelihood of certain events occurring. It is also used in decision making, risk assessment, and data analysis to make informed choices and predictions.

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