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  2. Probability density function - Wikipedia

    en.wikipedia.org/wiki/Probability_density_function

    This substantially unifies the treatment of discrete and continuous probability distributions. The above expression allows for determining statistical characteristics of such a discrete variable (such as the mean, variance, and kurtosis), starting from the formulas given for a continuous distribution of the probability.

  3. Game complexity - Wikipedia

    en.wikipedia.org/wiki/Game_complexity

    Game-tree complexity of a game is the number of leaf nodes in the smallest full-width decision tree that establishes the value of the initial position. [1] A full-width tree includes all nodes at each depth. This is an estimate of the number of positions one would have to evaluate in a minimax search to determine the value of the initial position.

  4. Shapley value - Wikipedia

    en.wikipedia.org/wiki/Shapley_value

    Formally, a coalitional game is defined as: There is a set N (of n players) and a function that maps subsets of players to the real numbers: :, with () =, where denotes the empty set. The function v {\displaystyle v} is called a characteristic function.

  5. (a,b,0) class of distributions - Wikipedia

    en.wikipedia.org/wiki/(a,b,0)_class_of_distributions

    Furthermore, it was shown by Fackler [2] that there is a universal formula for all three distributions, called the (united) Panjer distribution. The more usual parameters of these distributions are determined by both a and b. The properties of these distributions in relation to the present class of distributions are summarised in the following ...

  6. Gambling mathematics - Wikipedia

    en.wikipedia.org/wiki/Gambling_mathematics

    The mathematics of gambling is a collection of probability applications encountered in games of chance and can get included in game theory.From a mathematical point of view, the games of chance are experiments generating various types of aleatory events, and it is possible to calculate by using the properties of probability on a finite space of possibilities.

  7. Chi-squared distribution - Wikipedia

    en.wikipedia.org/wiki/Chi-squared_distribution

    Approximate formula for median (from the Wilson–Hilferty transformation) compared with numerical quantile (top); and difference (blue) and relative difference (red) between numerical quantile and approximate formula (bottom). For the chi-squared distribution, only the positive integer numbers of degrees of freedom (circles) are meaningful.

  8. Chegg stock crashes as free AI tools send online education ...

    www.aol.com/finance/chegg-stock-crashes-free-ai...

    Chegg stock has lost nearly 70% over the last year and has been roughly cut in half in 2024. From its peak in 2021, the stock is down over 95%. Since the launch of ChatGPT in late 2022 the company ...

  9. Likelihood function - Wikipedia

    en.wikipedia.org/wiki/Likelihood_function

    More generally, for each value of , we can calculate the corresponding likelihood. The result of such calculations is displayed in Figure 1. The result of such calculations is displayed in Figure 1. The integral of L {\textstyle {\mathcal {L}}} over [0, 1] is 1/3; likelihoods need not integrate or sum to one over the parameter space.