We can do more than just calculate the probability of pulling exactly 3 red marbles in 5 total pulls. For any binomial random variable, we can also calculate something like the probability of pulling at least 3 red marbles, or the probability of pulling no more than 3 marbles.
Read MoreRemember that for a binomial random variable X, we’re looking for the number of successes in a finite number of trials. For a geometric random variable, most of the conditions we put on the binomial random variable still apply: 1) each trial must be independent, 2) each trial can be called a “success” or “failure,” and 3) the probability of success on each trial is constant.
Read MoreRemember that “bi” means two, so a binomial variable is a variable that can take on exactly two values. A coin is the most obvious example of a binomial variable because flipping the coin can only result in two values: heads or tails.
Read MoreA Bernoulli random variable is a special category of binomial random variables. Specifically, with a Bernoulli random variable, we have exactly one trial only (binomial random variables can have multiple trials), and we define “success” as a 1 and “failure” as a 0.
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