Calculate basic probability for single and combined events. Compute AND, OR, NOT probabilities and conditional probability. Free online probability calculator.
The Probability Calculator helps you compute basic event probabilities. Enter the probability of events A and B, then instantly get the probability of both (A AND B), either (A OR B), not A, not B, and conditional probabilities.
Probability is the mathematical framework for quantifying uncertainty. From weather forecasts to medical tests to card games, probability theory provides the tools to reason about uncertain outcomes.
This calculator handles independent events (AND = P(A) × P(B)) and the addition rule (OR = P(A) + P(B) − P(A AND B)), plus complements. Enter probabilities as values between 0 and 1.
Integrating this calculation into regular planning habits ensures that work priorities reflect actual data about where time and energy produce the greatest results each week. Precise measurement of this value supports better personal and professional planning, helping you make informed decisions about how to prioritize tasks and manage competing demands.
Integrating this calculation into regular planning habits ensures that work priorities reflect actual data about where time and energy produce the greatest results each week.
Combining probabilities correctly requires knowing the right formula (AND, OR, NOT). This calculator applies the rules automatically and shows results for all common combinations. Precise quantification supports meaningful goal-setting and accountability, ensuring that improvement efforts are focused on areas with the greatest potential impact on output. Data-driven tracking enables proactive schedule management, helping professionals protect focused work time and reduce the cognitive overhead of constant task-switching throughout the day.
P(A AND B) = P(A) × P(B) (independent events) P(A OR B) = P(A) + P(B) − P(A AND B) P(NOT A) = 1 − P(A)
Result: P(A AND B) = 0.15, P(A OR B) = 0.65
P(A AND B) = 0.3 × 0.5 = 0.15. P(A OR B) = 0.3 + 0.5 − 0.15 = 0.65. P(NOT A) = 0.7. P(NOT B) = 0.5.
Weather forecasts, sports odds, insurance premiums, and medical test accuracy all rely on probability. Understanding basic probability helps you evaluate risks and make better decisions.
The gambler's fallacy is the belief that past results affect independent future events. A coin has a 50% chance of heads regardless of the previous 10 flips.
Modern probability theory, formalized by Kolmogorov in 1933, defines probability as a measure satisfying three axioms: non-negativity, normalization (total = 1), and countable additivity for mutually exclusive events.
Professionals in data science, engineering, and finance apply these calculations daily to model complex systems and test analytical hypotheses.
Probability is a number between 0 and 1 that represents how likely an event is to occur. 0 means impossible, 1 means certain, and 0.5 means equally likely as not.
Two events are independent if the occurrence of one does not affect the probability of the other. Flipping a coin twice produces independent events.
P(A OR B) = P(A) + P(B) − P(A AND B). The subtraction prevents double-counting the overlap where both events occur.
P(A|B) is the probability of A given that B has occurred. For independent events, P(A|B) = P(A). For dependent events, P(A|B) = P(A AND B) / P(B).
Use the complement: P(at least one) = 1 − P(none). For example, P(at least one head in 3 flips) = 1 − (0.5)³ = 0.875.
Bayes' theorem computes P(A|B) from P(B|A): P(A|B) = P(B|A) × P(A) / P(B). It is fundamental in medical testing, spam filtering, and machine learning.