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Sample spaces and the axioms

Kolmogorov's axioms, events as sets, conditional probability and Bayes.

Probability is a measure on events: non-negative, total 1, additive over disjoint events. Conditional probability P(A|B) = P(A ∩ B)/P(B), and Bayes reverses the conditioning. Picture it: a tree diagram; multiply along branches, add across leaves. Think it: the axioms are measure theory with total mass 1, which is why the two subjects merged.

Nhazi ahụ ejirila · 1 - (5/6)^4

Arithmetic · Arithmetic

Evaluate 1 - (5/6)^4

1 - \left(\frac{5}{6}\right)^{4}

Nzọụkwụ site n'ụdị

  1. 1 - \left(\frac{5}{6}\right)^{4} = 1 - \frac{625}{1296}

    Power: (5/6)^4 = 625/1296.

  2. 1 - \frac{625}{1296} = \frac{671}{1296}

    Simplify.

Gosi nzaghachi
\frac{671}{1296} \approx 0.51775

Ugbu a ị Họrọ nsogbu, mọọbụ tinye mọọbụ depụta gị. Nzọụkwụ ọbụla, inyogo, azịza ahụ echekwara ruo mgbe ịjụla.

Kwụsị ọrụ gị

Akwụkwọ ndebanye n'efu na-egbakwunye ntọala n'ụdị ọmụmụ ihe ọbụla, ndepụta nke ihe ị ga-eme, nsogbu ị ga-ewepụ n'otu ebe, na onye nkụzi ị ga-ajụ banyere ihuakwụkwọ a. Akwụkwọ ndepụta ihe bụ nke ọbụla mepere maka onye ọbụla, ọbụla ma ọ bụ na ọ bụghị.

Akaụntụ Nbanye

Aịkọn ndị ahụ ejirila ebe a

Tinye ọbụla simbụl maka nkọwa zuru ezu, inyogo, na ihe ọbụla ọbụla na-egosi.

Olee otú: Sample spaces and the axioms

  1. Power: (5/6)^4 = 625/1296.
  2. Simplify.

Ajụjụ ndị mmadụ jụrụ

What is the difference between probability and statistics?

Probability goes from a known model to what the data should look like; statistics goes from data back to the model. Probability theory is the deductive half.

What does the law of large numbers promise?

That the average of many independent samples converges to the expected value. It says nothing about any single trial.

Oge Probability Theory

Random variables and expectationThe common distributionsThe law of large numbers and the central limit theorem