When can a binomial distribution be normally distributed?

When can a binomial distribution be normally distributed?

The normal distribution can be used as an approximation to the binomial distribution, under certain circumstances, namely: If X ~ B(n, p) and if n is large and/or p is close to ½, then X is approximately N(np, npq)

What happens as the value of n increases and p remains the same?

What happens as the value of n increases and the probability of success remains the same? A. As n increases, the distribution becomes more symmetric.

What is not a binomial experiment?

Examples of experiments that are not Binomial Experiments Tossing a coin until you get a heads (it could take one toss, or three, or six, so there is not a fixed number of trials). This is actually called a negative binomial experiment.

How is the binomial distribution related to probability?

The binomial distribution determines the probability of observing a specified number of successful outcomes in a specified number of trials.

What is the binomial distribution in a Bernoulli trial?

Bernoulli Trial. The binomial distribution is the sum of a series of multiple independent and identically distributed Bernoulli trials. In a Bernoulli trial, the experiment is said to be random and could only have two possible outcomes: success or failure.

How to create a reference table for binomial distribution?

In creating reference tables for binomial distribution probability, usually the table is filled in up to n/2 values. f ( k , n , p ) = f ( n − k , n , 1 − p ) .

When to use a binomial or hypergeometric distribution?

The binomial distribution is frequently used to model the number of successes in a sample of size n drawn with replacement from a population of size N. If the sampling is carried out without replacement, the draws are not independent and so the resulting distribution is a hypergeometric distribution, not a binomial one.