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.
Akaunti la bure laongezea mambo makuu juu ya kila somo, rekodi ya yale ambayo umemaliza, matatizo yako ya kutatua katika sehemu moja, na mtunzaji unayeweza kuuliza juu ya ukurasa huu.
Vaa alama yoyote ya ufafanuzi kamili, picha, na maana ya kila herufi.
Maana ya kila sehemu
Wazia hilo
Inastahili Kujua
Vielelezo
Pia, ufafanuzi huo ulitumiwa
Jinsi ya Kufaulu: Sample spaces and the axioms
Power: (5/6)^4 = 625/1296.
Simplify.
Maswali ambayo watu huuliza
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.