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#reading-9-probability-concepts

When two random variables are independent, the joint probability function is the product of the individual probability functions of the random variables.

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**Summary **

Rj) . The calculation of covariance in a forward-looking sense requires the specification of a joint probability function, which gives the probability of joint occurrences of values of the two random variables. <span>When two random variables are independent, the joint probability function is the product of the individual probability functions of the random variables. Bayesâ€™ formula is a method for updating probabilities based on new information. Bayesâ€™ formula is expressed as follows: Updated probability of event give

Rj) . The calculation of covariance in a forward-looking sense requires the specification of a joint probability function, which gives the probability of joint occurrences of values of the two random variables. <span>When two random variables are independent, the joint probability function is the product of the individual probability functions of the random variables. Bayesâ€™ formula is a method for updating probabilities based on new information. Bayesâ€™ formula is expressed as follows: Updated probability of event give

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