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  2. Sample space - Wikipedia

    en.wikipedia.org/wiki/Sample_space

    The probability of the event that the sum + is five is , since four of the thirty-six equally likely pairs of outcomes sum to five. If the sample space was all of the possible sums obtained from rolling two six-sided dice, the above formula can still be applied because the dice rolls are fair, but the number of outcomes in a given event will vary.

  3. Small-bias sample space - Wikipedia

    en.wikipedia.org/wiki/Small-bias_sample_space

    where the sum is taken over , the finite field with two elements. In other words, the sum ∑ i ∈ I x i {\displaystyle \sum _{i\in I}x_{i}} equals 0 {\displaystyle 0} if the number of ones in the sample x ∈ { 0 , 1 } n {\displaystyle x\in \{0,1\}^{n}} at the positions defined by I {\displaystyle I} is even, and otherwise, the sum equals 1 ...

  4. Zero-sum game - Wikipedia

    en.wikipedia.org/wiki/Zero-sum_game

    For the example given above, it turns out that Red should choose action 1 with probability4 / 7 ⁠ and action 2 with probability ⁠ 3 / 7 ⁠, and Blue should assign the probabilities 0, ⁠ 4 / 7 ⁠, and ⁠ 3 / 7 ⁠ to the three actions A, B, and C. Red will then win ⁠ 20 / 7 ⁠ points on average per game.

  5. Probability space - Wikipedia

    en.wikipedia.org/wiki/Probability_space

    If this sum is equal to 1 then all other points can safely be excluded from the sample space, returning us to the discrete case. Otherwise, if the sum of probabilities of all atoms is between 0 and 1, then the probability space decomposes into a discrete (atomic) part (maybe empty) and a non-atomic part.

  6. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    For instance, if X is used to denote the outcome of a coin toss ("the experiment"), then the probability distribution of X would take the value 0.5 (1 in 2 or 1/2) for X = heads, and 0.5 for X = tails (assuming that the coin is fair). More commonly, probability distributions are used to compare the relative occurrence of many different random ...

  7. Urn problem - Wikipedia

    en.wikipedia.org/wiki/Urn_problem

    In this basic urn model in probability theory, the urn contains x white and y black balls, well-mixed together. One ball is drawn randomly from the urn and its color observed; it is then placed back in the urn (or not), and the selection process is repeated. [3] Possible questions that can be answered in this model are:

  8. 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 ÷ 6/9 = 4/6. Likewise ...

  9. Empty sum - Wikipedia

    en.wikipedia.org/wiki/Empty_sum

    In mathematics, an empty sum, or nullary sum, [1] is a summation where the number of terms is zero. The natural way to extend non-empty sums [ 2 ] is to let the empty sum be the additive identity . Let a 1 {\displaystyle a_{1}} , a 2 {\displaystyle a_{2}} , a 3 {\displaystyle a_{3}} , ... be a sequence of numbers, and let

  1. Related searches sum if fill color equals 0 then find the probability of giving 20 or 4

    sum if fill color equals 0 then find the probability of giving 20 or 4 percent