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  2. Birthday problem - Wikipedia

    en.wikipedia.org/wiki/Birthday_problem

    Comparing p(n) = probability of a birthday match with q(n) = probability of matching your birthday. In the birthday problem, neither of the two people is chosen in advance. By contrast, the probability q(n) that at least one other person in a room of n other people has the same birthday as a particular person (for example, you) is given by

  3. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    The Rademacher distribution, which takes value 1 with probability 1/2 and value −1 with probability 1/2. The binomial distribution, which describes the number of successes in a series of independent Yes/No experiments all with the same probability of success.

  4. Orders of magnitude (probability) - Wikipedia

    en.wikipedia.org/wiki/Orders_of_magnitude...

    Probability of a random day of the year being your birthday (for all birthdays besides Feb. 29) 4×10 −3: Probability of being dealt a straight in poker 10 −2: Centi-(c) 1.8×10 −2: Probability of winning any prize in the UK National Lottery with one ticket in 2003 2.1×10 −2: Probability of being dealt a three of a kind in poker 2.3× ...

  5. Wikipedia:Reference desk/Science/Birthday probability ...

    en.wikipedia.org/.../Birthday_probability_question

    (1/365! is the probability that you take 365 people with distinct birthdays and, picking them one at a time, correctly pick them in birthday order). Let's work with smaller numbers: assume a 3-sided coin (it's more interesting than a two-sided, but the numbers are small).

  6. Conditional probability table - Wikipedia

    en.wikipedia.org/wiki/Conditional_probability_table

    The first column sum is the probability that x =0 and y equals any of the values it can have – that is, the column sum 6/9 is the marginal probability that x=0. If we want to find the probability that y=0 given that x=0, we compute the fraction of the probabilities in the x=0 column that have the value y=0, which is 4/9 ÷

  7. Actuarial notation - Wikipedia

    en.wikipedia.org/wiki/Actuarial_notation

    In a life table, we consider the probability of a person dying between age (x) and age x + 1; this probability is called q x. In the continuous case, we could also consider the conditional probability that a person who has attained age (x) will die between age (x) and age (x + Δx) as:

  8. Hash collision - Wikipedia

    en.wikipedia.org/wiki/Hash_collision

    When there is a set of n objects, if n is greater than |R|, which in this case R is the range of the hash value, the probability that there will be a hash collision is 1, meaning it is guaranteed to occur. [4] Another reason hash collisions are likely at some point in time stems from the idea of the birthday paradox in mathematics.

  9. Kish grid - Wikipedia

    en.wikipedia.org/wiki/Kish_grid

    This statistics -related article is a stub. You can help Wikipedia by expanding it.