maths.free › Probability Theory › Sample spaces and the axioms

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.

Kushanda muenzaniso · 1 - (5/6)^4

Arithmetic · Arithmetic

Evaluate 1 - (5/6)^4

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

Step by step

  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.

Kuratidza mhinduro
\frac{671}{1296} \approx 0.51775

Zvino iwe Choose a problem, or type or draw your own. Every step, a picture, the answer hidden until you ask.

Tenga yako yemahara

Mubhadharo wakasununguka unowedzera mazita ezvidzidzo, zvinyorwa zvezvidzidzo zvawakati wazvigadzirira, zvidzidzo zvawave uchizvigadzirisa, uye mudzidzisi waungabvunza nezvechidzidzo ichi. Maths inowanikwa kune vese, vasiri vadzidzi kana vadzidzi. Kuwana mazita ezvidzidzo zvinodiwa kunogona kuitwa pawebsite ye Maths.

Kutanga Kupinda

Mazita anoshandiswa pano

Tinya chero chiratidzo kuti uone chirevo chakazara, vhidhiyo, uye kuti chii chinoreva chero chiratidzo.

Maitiro: Sample spaces and the axioms

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

Mabvunzo vanhu vanobvunza

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.

More in Probability Theory

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