standardizing a random variable if
Standardizing a Random Variable
If X is a random variable with E(X) = m and V(X) = s2, then Y = (X – m)/ s is a random variable with mean 0 and standard deviation 1.
The standardization (or normalization) of X results in Y.
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random variable a variable which assumes different numerical values as a result of random experiments or random occurrences is known as a random
probability distributionssince the value of a random variable cannot be predicted accurately by convention probabilities are assigned to all the
how is the probability distribution of a random variable constructedusually the past behavior of the variable is studied and the frequency
expected valuefor taking decisions under conditions of uncertainty the concept of expected value of a random variable is used the expected value
standardizing a random variable if x is a random variable with ex m and vx s2 then y x ndash m s is a random variable with mean 0
continuous random variablein the probability distribution the sum of all the probabilities was 1consider the variable x denoting volume poured into a
covariance the variance is a measure of the variability or dispersion in a variable or data seta measure of the variability of one variable or data
discrete uniform distributionacme limited is a car manufacturer the company can paint the car in 3 possible colors white black and blue until the
the lognormal distributionif lnx is a normally distributed random variable then x is said to be a lognormal variableif p1 p2 p3 are the prices of a
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