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Event Probability P(A)
0.1667
16.67% (1 in 6.0 chance)
Standard Kolmogorov axiomatic probability distribution.

Fundamentals of Mathematical Probability Theory

Probability is the quantitative measurement of the likelihood that an event will occur in a random experiment, bounded on the real interval $[0, 1]$, where 0 signifies an impossible event and 1 signifies absolute certainty.

Core Probability Theorems and Rules

Probability Concept Standard Formula Description
Complement Rule $P(A') = 1 - P(A)$ Probability that event A does not happen
Multiplication Rule (Independent) $P(A \cap B) = P(A) \times P(B)$ Probability that both events A and B happen together
Addition Rule (General) $P(A \cup B) = P(A) + P(B) - P(A \cap B)$ Probability that at least one event (A or B) occurs
Binomial Probability Mass Function $P(X = k) = \binom{n}{k} p^k (1-p)^{n-k}$ Probability of exactly $k$ successes in $n$ Bernoulli trials