Another proof using the axioms of probability

In summary, the conversation discusses using the axioms of probability to show that if B is a subset of A, then the probability of B is less than or equal to the probability of A. The proof involves defining A using the law of total probability and applying axiom 3, and considering the equality case where P(A ∩ Bc)=0. It is determined that this does not necessarily mean A=B, as demonstrated by an example.
  • #1
phosgene
146
1

Homework Statement



If A and B are events, use the axioms of probability to show that:

[itex]if B \subset A, then P(B) \leq P(A)[/itex]

Homework Equations



Axiom 1: [itex]P(n) \geq 0[/itex]

Axiom 2: [itex]P(S)=1[/itex]

Axiom 3: If A1,A2,... are disjoint sets, then [itex]P(\bigcup _{i} A_{i}) = \sum_{i} P(A_{i})[/itex]

The Attempt at a Solution



I start with using the law of total probability to define the set A:

[itex]A= (A \cap B) \cup (A \cap B^{C})[/itex]

Then I use axiom 3 to get turn it into a probability:

[itex]P(A) = P(A \cap B) + P(A \cap B^{C})[/itex]

Since [itex]B \subset A, P(A \cap B) = P(B)[/itex]

So

[itex]P(A) = P(B) + P(A \cap B^{C})[/itex]

[itex]P(B)=P(A) - P(A \cap B^{C})[/itex]

And as axiom 1 states that a probability must be greater than or equal to 0,

[itex]P(B) \leq P(A)[/itex]

As for proving the equality case, this means that [itex]P(A \cap B^{C}) = 0[/itex], but then doesn't that just mean that A=B. Since the question states that B is a *proper* subset of A, am I incorrect in thinking that it might be a typo?
 
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  • #2
phosgene said:
And as axiom 1 states that a probability must be greater than 0
It says the probability must be greater than or equal to 0.
 
  • #3
Ok, fixed. But suppose that [itex]P(A \cap B^{C}) = 0[/itex], doesn't this mean that A=B?
 
  • #4
Not necessarily. For example, say you have a continuous random variable X that's uniformly distributed on [0,1]. Let A=[0,1] and B=(0,1). Both P(A)=P(B)=1, but A≠B.
 
  • #5
[itex][/itex]I see, interesting..so basically, using axiom 1, I will get [itex]P(B) \leq P(A)[/itex], which completes my proof. Thanks :)
 

1. What are the axioms of probability?

The axioms of probability are three basic principles that govern the rules of probability. They include the axiom of non-negativity, which states that the probability of an event cannot be negative; the axiom of total probability, which states that the sum of all possible outcomes must equal 1; and the axiom of additivity, which states that the probability of two mutually exclusive events occurring is equal to the sum of their individual probabilities.

2. How are the axioms of probability used in proofs?

The axioms of probability are used as the foundation for mathematical proofs in probability theory. By starting with these basic principles, we can build upon them to prove more complex theorems and formulas.

3. What is the purpose of using axioms in probability?

The purpose of using axioms in probability is to establish a set of fundamental rules that govern the behavior of probabilities. These axioms provide a logical and consistent framework for understanding and analyzing uncertain events.

4. Can the axioms of probability be proven?

No, the axioms of probability cannot be proven. They are considered to be self-evident truths that serve as the foundation for probability theory. However, they can be used to prove other theorems and formulas.

5. Are there alternative axioms of probability?

Yes, there are alternative axioms of probability that have been proposed, such as the Cox axioms and the de Finetti coherence axioms. These axioms aim to provide a more general and abstract framework for probability theory, but the traditional axioms are still widely used and accepted.

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