Layout for defining prob. for Independent Events.

In summary, the problem is that I am trying to show that the probability of team A winning two consecutive games is (0.6)^2 , arguing that the outcome : AA has probability (0.6)(0.6) . However, I am having trouble expressing 'AA' as an intersection of two events.
  • #1
Bacle
662
1
Hi, everyone:

I was reviewing some intro material, and I ended up confused with the issue of

independence with the following problem:

We are given two teams, A,B, playing against each other. A wins with probability

P(A)=0.6 , B wins with P(B)=0.4 (games are played until someone wins.). We also

assume that the outcome of any game is independent from that of any other

game.


**Now** . Here is where I am confused:

Let a string with A in i-th place and B in j-th place denote that A won the i-th

game and B won the j-th game.

I am trying to show that the probability of team A winning two consecutive games

is (0.6)^2 , arguing that the outcome : AA has probability (0.6)(0.6) , since the

outcome of game 2 is (assumed) independent from that of game 1.

**BUT** I am having trouble expressing the event 'AA' as an intersection of two

events E,E' , which I need to do in order to use the rule: P(E/\E')=P(E)*P(E') , (with

/\:= intersection , and * is product)

My sample space is :

{ A,B , AA, AB, BA, BB, AAA, ...}


And I don't see how to express 'AA' as an intersection of events in order to justify

saying that the probability of 'AA' is (0.6)(0.6) . Any Ideas.?.

Thanks.
 
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  • #2
You are confusing the teams A and B with the events A wins or B wins. The outcome of the first game may be called O1 and the second game O2. So the independent events of interest are Oi=A wins for i=1 and 2.
So P(O1=A wins and O2=A wins)=P(O1=A wins)P(O2=A wins).
 
  • #3
""You are confusing the teams A and B with the events A wins or B wins."


Not really. I described my choice of notation:


" Let a string with A in i-th place and B in j-th place denote that A won the i-th

game and B won the j-th game."


By this notation, a string AA denotes the team A winning twice consecutively.


But the issue I had was that my options for deriving a probability were:

0) Define the sample space S. Then an event E is an element in 2^S.

i) P(E union E')=P(E)+P(E')

ii) P (E intersection E') =P(E)*p(E')

And I do not see any way of expressing 'AA' as neither of i nor ii).
 
  • #4
Your notation is what is making it difficult for yourself. Let A1 be the event A won the first game and A2 be the event A won the second game. So P(A1 and A2) = P(A1)P(A2).
 
  • #5
No. The point is I can only use strict set intersection, or strict set union,

and not the informal ( but sometimes equivalent) 'E or E' , or E intersection E'.

Can you express the event of A winning twice as a _set intersection_ of

events.?.

I mean, define a sample space S of all outcomes, then take 2^S to be the

set of events.

Can you then express A winning twice as an intersection of any two elements in 2^S.?.


I don't mean in the form 'A and B' , but as an actual intersection of elements of 2^S.
 
  • #6
Just to clarify my approach:

My sample space would be :

{A,B ; AA, AB, BA, BB ; AAA, AAB, ABA, ABB, BBB, ,BAA, BAB, BBA...}

And I don't see how 'AA' itself is an intersection. I am trying to avoid

product spaces.


I can see how to use intersection when, e.g., I throw a single fair

die, and I get the sample space : {1,2,3,4,5,6} , then 2^S is my

sample space, and the event : "even and larger than 3" is the intersection

of , e.g., { 2,4,6} and {4,6}. But once I throw the die twice , expressing

outcomes as intersections becomes more difficult. Can you express

an event as an intersection in this case.?
 
  • #7
Each trial is a possible event, so a particular result of two trials is the intersection of the outcomes of each trial.
 

1. What is a layout for defining probabilities for independent events?

A layout for defining probabilities for independent events is a systematic way of organizing and analyzing the outcomes of independent events. It involves identifying all possible outcomes and assigning a probability to each outcome based on the likelihood of its occurrence.

2. How do you determine the probability of an outcome in a layout for independent events?

The probability of an outcome in a layout for independent events is determined by dividing the number of favorable outcomes by the total number of possible outcomes. This can be represented mathematically as P(A) = number of favorable outcomes / total number of possible outcomes.

3. What is meant by independent events in a layout for defining probabilities?

Independent events refer to events that do not affect each other's outcomes. This means that the occurrence of one event does not impact the probability of the other event occurring. In a layout for defining probabilities, this is represented by separate branches or columns for each event.

4. How is a layout for defining probabilities for independent events used in real-life scenarios?

A layout for defining probabilities for independent events is commonly used in gambling, insurance, and other risk management industries to calculate the likelihood of certain outcomes. It can also be used in scientific experiments and surveys to analyze data and make predictions.

5. Are there any limitations to using a layout for defining probabilities for independent events?

Yes, there are some limitations to using a layout for defining probabilities for independent events. It assumes that all outcomes are equally likely, which may not always be the case in real-life scenarios. It also does not account for any external factors that may influence the outcomes of the events.

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