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Presentation 1-2-1: Of Axioms and Algebras Primary reference: Casella-Berger 2 nd Edition Presentation 1-2-1: Of Axioms and Algebras (the sample space) And in it were (of an experiment) dj vu? 2 Presentation 1-2-1: Of Axioms


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Presentation 1-2-1: Of Axioms and Algebras

Primary reference: Casella-Berger 2nd Edition

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Presentation 1-2-1: Of Axioms and Algebras

(the sample space)

And in it were…

(of an experiment) …déjà vu?

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If you rolled a die with these six faces 100 times… …you might expect a different outcome than you’d get from

  • ne with these six faces.

So maybe probability could be interpreted in terms of the frequency of occurrence of certain outcomes of an experiment?

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How many times can you repeat an election? So maybe interpretation of probability is more subjective?

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We don’t need no stinking context when we got cold, hard axioms! For now, we don’t need to interpret probabilities, we just gotta make sure they follow the rules.

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But before we can talk about the axioms of probability, first we need to talk about parallel universes. (nah just sigma algebras)

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First, it gets a fancy letter: ℬ Second, it’s a term for a collection

  • f subsets of our sample space Ω

that has special properties!

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  • a. ∅ ∈ ℬ : It ain’t a Borel field unless the empty set is an element!
  • b. For any set 𝐵, if 𝐵 ∈ ℬ, then 𝐵𝐷 ∈ ℬ. Remember, 𝐵𝐷 is the

complement of A! This property is known as being closed under complementation!

  • c. If sets 𝐵1, 𝐵2, 𝐵3, … ∈ ℬ, then

ڂ𝑗=1

∞ 𝐵𝑗 ∈ ℬ

This property is known as being closed under countable unions!

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  • a. ∅ ∈ ℬ

So the empty set is in ℬ. Big deal, right? ∅ is a subset of every set. But, ∅ = Ω𝑑, and rule b. said ℬ had to be closed under complementation! So now Ω is always in ℬ, too!

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  • c. If sets 𝐵1, 𝐵2, 𝐵3, … ∈ ℬ, then

ڂ𝑗=1

∞ 𝐵𝑗 ∈ ℬ

Oh boy, things get tricky for a bit. By rule b. (closed under complementation), ڂ𝑗=1

∞ 𝐵𝑗 𝐷 ∈ ℬ too! Plus, 𝐵1 𝐷, 𝐵2 𝐷, 𝐵3 𝐷, … ∈ ℬ.

Applying rule c. once more means ڂ𝑗=1

∞ 𝐵𝑗 𝐷 ∈ ℬ, and a final

application of rule b. means ڂ𝑗=1

∞ 𝐵𝑗 𝐷 𝐷 ∈ ℬ!

(is the room spinning, or just my head?!)

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Remember DeMorgan’s Law? It states that for any sets 𝐵1 and 𝐵2,

(𝐵1∪𝐵2)C= 𝐵1

𝐷 ∩ 𝐵2 𝐷.

Well, that law can be shown to prove that ڂ𝑗=1

∞ 𝐵𝑗 𝐷 𝐷 =ځ𝑗=1 ∞ 𝐵𝑗, so now the intersection of all those sets is by

definition an element of ℬ.

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  • 1. ∅ ∈ ℬ
  • 2. Ω ∈ ℬ
  • 3. If sets 𝐵1, 𝐵2, 𝐵3, … ∈ ℬ,

a)ڂ𝑗=1

∞ 𝐵𝑗 ∈ ℬ

b)ڂ𝑗=1

∞ 𝐵𝑗 𝐷 ∈ ℬ

c) 𝐵1

𝐷, 𝐵2 𝐷, 𝐵3 𝐷, … ∈ ℬ

d)ڂ𝑗=1

∞ 𝐵𝑗 𝐷 ∈ ℬ

e)ڂ𝑗=1

∞ 𝐵𝑗 𝐷 𝐷 =ځ𝑗=1 ∞ 𝐵𝑗 ∈ ℬ

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For all of that misery, we’re only interested in the smallest Borel field that contains all the open sets of Ω. If the elements of Ω are finite or at least countable, then this is just all the subsets of Ω, including Ω itself.

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Ω = {x, y, z}

Ok, so let’s define a little sample space again, and figure out which sets go into our Borel field.

  • 1. ∅
  • 2. {x, y, z}
  • 3. {x}
  • 4. {y}
  • 5. {z}
  • 6. {x, y}
  • 7. {x, z}
  • 8. {y, z}

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…you don’t want to know.

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And so you shall, my friend! For now, I shall unveil to you Kolmogorov’s axioms of probability, though

  • nly to whet your appetite for the decadent

mathematical pleasures yet to come! Now for the moment you’ve been waiting for, here they are!

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  • 1. P(𝐵) ≥ 0 for all 𝐵 ∈ ℬ
  • 2. P(Ω) = 1
  • 3. If sets 𝐵1, 𝐵2, 𝐵3, … ∈ ℬ are pairwise disjoint,

then P(ڂ𝑗=1

∞ 𝐵𝑗) = σ𝑗=1 ∞ 𝑄(𝐵𝑗)

(okay bye)

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