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Definition of binomial random variable, from the Stat Trek dictionary of statistical terms and concepts. This statistics glossary includes definitions of all technical terms used on Stat Trek website.


binomial random variable: A type of discrete random variable used to count the number of occurrences of an event in a random sample in a binomial experiment. A binomial random variable can only be used to count whether a certain event occurs or does not occur, and cannot be used to measure partial states.


In general, if the random variable X follows the binomial distribution with parameters n ∈ ℕ and p ∈ [0,1], we write X ~ B(n, p). The probability of getting exactly k successes in n trials is given by the probability mass function:


A binomial random variable is a count of the number of successes in a binomial experiment. Rolling dice can be a binomial experiment under the right conditions. For a variable to be classified as a binomial random variable, the following conditions must all be true:


X is a binomial random variable with n = 4 and p = 0.4. As a review, let’s first find the probability distribution of X the long way: construct an interim table of all possible outcomes in S, the corresponding values of X, and probabilities. Then construct the probability distribution table for X.


Remember, the binomial random variable is the number of successes in a binomial experiment. We can find the mean, or the average expected number, of successes in Jennifer's experiment. Jennifer ...


A random variable is binomial if the following four conditions are met: There are a fixed number of trials (n). Each trial has two possible outcomes: success or failure. The probability of success (call it p) is the same for each trial.


The Binomial Random Variable The Binomial Formula The binomial distribution is a discrete probability distribution of the successes in a sequence of [latex]\text{n}[/latex] independent yes/no experiments.


Distribution of a sum of geometrically distributed random variables. If Y r is a random variable following the negative binomial distribution with parameters r and p, and support {0, 1, 2, ...}, then Y r is a sum of r independent variables following the geometric distribution (on {0, 1, 2, ...}) with parameter 1 − p.


And this random variable, it could take on the value x equals zero, one, two, three, four or five. And I what want to do is figure out what's the probability that this random variable takes on zero, can be one, can be two, can be three, can be four, can be five.