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  2. Probability - Wikipedia

    en.wikipedia.org/wiki/Probability

    The probability of an event is a number between 0 and 1; the larger the probability, the more likely an event is to occur. [ note 1 ] [ 1 ] [ 2 ] This number is often expressed as a percentage (%), ranging from 0% to 100%.

  3. Lottery mathematics - Wikipedia

    en.wikipedia.org/wiki/Lottery_mathematics

    Lottery mathematics is used to calculate probabilities ... the ticket holder is a jackpot winner—regardless of the order of the numbers. The probability of this ...

  4. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    Diagram showing the cumulative distribution function for the normal distribution with mean (μ) 0 and variance (σ 2) 1. These numerical values "68%, 95%, 99.7%" come from the cumulative distribution function of the normal distribution.

  5. Expected value - Wikipedia

    en.wikipedia.org/wiki/Expected_value

    The expected value of a random variable with a finite number of outcomes is a weighted average of all possible outcomes. In the case of a continuum of possible outcomes, the expectation is defined by integration. In the axiomatic foundation for probability provided by measure theory, the expectation is given by Lebesgue integration.

  6. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    A discrete probability distribution is the probability distribution of a random variable that can take on only a countable number of values [15] (almost surely) [16] which means that the probability of any event can be expressed as a (finite or countably infinite) sum: = (=), where is a countable set with () =.

  7. Complex random variable - Wikipedia

    en.wikipedia.org/wiki/Complex_random_variable

    In probability theory and statistics, complex random variables are a generalization of real-valued random variables to complex numbers, i.e. the possible values a complex random variable may take are complex numbers. [1] Complex random variables can always be considered as pairs of real random variables: their real and imaginary parts.

  8. Pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_number_generator

    It can be shown that if is a pseudo-random number generator for the uniform distribution on (,) and if is the CDF of some given probability distribution , then is a pseudo-random number generator for , where : (,) is the percentile of , i.e. ():= {: ()}. Intuitively, an arbitrary distribution can be simulated from a simulation of the standard ...

  9. Coupon collector's problem - Wikipedia

    en.wikipedia.org/wiki/Coupon_collector's_problem

    Graph of number of coupons, n vs the expected number of trials (i.e., time) needed to collect them all E (T ) In probability theory, the coupon collector's problem refers to mathematical analysis of "collect all coupons and win" contests.