What Does P(A or B but Not Both) Represent in Probability?

In summary, P (A or B but not both (A and B)) can be written as P(A U B) - P(A intersect B), or P(A) + P(B) - 2P(A intersect B). This is shown in Venn diagrams by excluding the region that is common to both A and B, and can also be expressed as (A only) U (B only). It is helpful to use Venn diagrams to make generalizations in these types of situations.
  • #1
denian
641
0
what does this mean?

P (A or B but not both ( A and B ) ) ?

does it mean
P (A U B ) - P (A intersect B )?
 
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  • #2
Yes that is correct. By the way, do you know how to draw "Venn's diagram"? That would make things a bit easier.
 
  • #3
i ask that question because i see my friend work
she said it means

P ( A U B ) - 2 P ( A intersect B )

and she get the answer.
 
  • #4
Ok, I think it means P(A)+P(B)-2P(A intersects B).
 
  • #5
thats it. thanks.
 
  • #6
I believe your problem is essentially solved but it is helpful to construct Venn diagrams in such situations (as Wong suggested) to make some useful generalizations. Set theoretically, A or B but not not both A and B means that the region in the venn diagram that is common to both A and B is excluded (of course, the region described by the sample space - (A+B) is also excluded). This translates (in the "only" notation) to,

[tex]
(A only) \bigcup (B only)
[/tex]

which really is

[tex]
(A \bigcap B') \bigcup (A' \bigcap B)
[/tex]
 

FAQ: What Does P(A or B but Not Both) Represent in Probability?

1. What is probability?

Probability is a measure of the likelihood or chance of an event occurring. It is expressed as a number between 0 and 1, where 0 indicates impossibility and 1 indicates certainty.

2. How is probability calculated?

Probability is calculated by dividing the number of favorable outcomes by the total number of possible outcomes. This can be represented by the formula P(A) = n(A)/n(S), where P(A) is the probability of event A, n(A) is the number of favorable outcomes, and n(S) is the total number of possible outcomes.

3. What is the difference between theoretical and experimental probability?

Theoretical probability is based on mathematical calculations and assumes that all outcomes are equally likely. Experimental probability is based on actual results from an experiment or observation. It may differ from theoretical probability if the sample size is small or if there are external factors affecting the outcomes.

4. How do you interpret a probability value?

A probability value can be interpreted as a percentage or a fraction. For example, a probability of 0.5 can be interpreted as a 50% chance or a 1/2 chance of the event occurring.

5. What are some real-life applications of probability?

Probability is used in many fields, including statistics, economics, and science. It can be used to predict the likelihood of a certain outcome, make informed decisions, and analyze data. Some examples of real-life applications of probability include weather forecasting, risk analysis in insurance, and predicting the outcome of a sports game.

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