TyErd said:
TyErd said:
A binomial distribution is a probability distribution that describes the likelihood of a certain number of successes in a fixed number of independent trials, with a given probability of success for each trial.
The formula for calculating binomial probability is P(x) = (nCx)(px)(qn-x), where n is the number of trials, x is the number of successes, and p is the probability of success for each trial. q is equal to 1-p, the probability of failure.
To use the binomial distribution to find probability, you need to know the number of trials, the probability of success for each trial, and the desired number of successes. Plug these values into the binomial probability formula, P(x), and solve for the probability P(x).
A binomial distribution is used to model discrete data, where there are a specific number of outcomes (e.g. number of heads in 10 coin flips). A normal distribution, on the other hand, is used to model continuous data, where there is an infinite number of possible outcomes (e.g. height or weight).
The binomial distribution can be used to model real-life situations such as coin flips, test scores, and election results. It is also commonly used in quality control and market research.
