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  2. Joint product pricing - Wikipedia

    en.wikipedia.org/wiki/Joint_product_pricing

    In microeconomics, joint product pricing is the firm's problem of choosing prices for joint products, which are two or more products produced from the same process or operation, each considered to be of value. Pricing for joint products is more complex than pricing for a single product. To begin with, there are two demand curves.

  3. Joint probability distribution - Wikipedia

    en.wikipedia.org/wiki/Joint_probability_distribution

    The joint distribution encodes the marginal distributions, i.e. the distributions of each of the individual random variables and the conditional probability distributions, which deal with how the outputs of one random variable are distributed when given information on the outputs of the other random variable(s).

  4. Chain rule (probability) - Wikipedia

    en.wikipedia.org/wiki/Chain_rule_(probability)

    This rule allows one to express a joint probability in terms of only conditional probabilities. [4] The rule is notably used in the context of discrete stochastic processes and in applications, e.g. the study of Bayesian networks, which describe a probability distribution in terms of conditional probabilities.

  5. Marginal distribution - Wikipedia

    en.wikipedia.org/wiki/Marginal_distribution

    Joint and marginal distributions of a pair of discrete random variables, X and Y, dependent, thus having nonzero mutual information I(X; Y). The values of the joint distribution are in the 3×4 rectangle; the values of the marginal distributions are along the right and bottom margins.

  6. Conditional probability distribution - Wikipedia

    en.wikipedia.org/wiki/Conditional_probability...

    The conditional distribution contrasts with the marginal distribution of a random variable, which is its distribution without reference to the value of the other variable. If the conditional distribution of Y {\displaystyle Y} given X {\displaystyle X} is a continuous distribution , then its probability density function is known as the ...

  7. Distribution of the product of two random variables - Wikipedia

    en.wikipedia.org/wiki/Distribution_of_the...

    The distribution of the product of correlated non-central normal samples was derived by Cui et al. [11] and takes the form of an infinite series of modified Bessel functions of the first kind. Moments of product of correlated central normal samples. For a central normal distribution N(0,1) the moments are

  8. Likelihood function - Wikipedia

    en.wikipedia.org/wiki/Likelihood_function

    One example occurs in 2×2 tables, where conditioning on all four marginal totals leads to a conditional likelihood based on the non-central hypergeometric distribution. This form of conditioning is also the basis for Fisher's exact test .

  9. Marginal product - Wikipedia

    en.wikipedia.org/wiki/Marginal_product

    Average physical product (APP), marginal physical product (MPP) In economics and in particular neoclassical economics, the marginal product or marginal physical productivity of an input (factor of production) is the change in output resulting from employing one more unit of a particular input (for instance, the change in output when a firm's labor is increased from five to six units), assuming ...