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There are several ways to determine p, the probabilityof success. First is by trials, called relative frequency. Second, use the classical approach which is calculate how many times it can occur divided by the sample space. Third is subjective, an educated guess.

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The variance for the binomial probability distribution is?

n(p)(1-p) n times p times one minus p, where n is the number of outcomes in the binomial distribution, and p is the probability of a success.


How can you approximate a binomial distribution to a poison distribution when the number of binomial trials became large enough?

The Poisson distribution with parameter np will be a good approximation for the binomial distribution with parameters n and p when n is large and p is small. For more details See related link below


What is the parameters that determine a Binomial Distribution?

The binomial distribution has two parameter, denoted by n and p. n is the number of trials. p is the constant probability of "success" at each trial.


When can a binomial situation be approxiamted with a normal distribution?

The binomial distribution can be approximated with a normal distribution when np > 5 and np(1-p) > 5 where p is the proportion (probability) of success of an event and n is the total number of independent trials.


What has the author Sol Weintraub written?

Sol Weintraub has written: 'Tables of the cumulative binomial probability distribution for small values of p' -- subject(s): Binomial distribution, Tables


Assume that you have a binomial experiment with p 0.5 and a sample size of 100. The expected value of this distribution is?

In a binomial distribution, the expected value (mean) is calculated using the formula ( E(X) = n \times p ), where ( n ) is the sample size and ( p ) is the probability of success. For your experiment, with ( n = 100 ) and ( p = 0.5 ), the expected value is ( E(X) = 100 \times 0.5 = 50 ). Thus, the expected value of this binomial distribution is 50.


What are uses of binomial distribution in psychology?

what are the uses of binomial distribution


What are mean and variance of negative binomial distribution by conclusion?

what is meant by a negative binomial distribution what is meant by a negative binomial distribution


How do you do binomial distribution?

You distribute the binomial.


How is poisson distribution related to binomial distribution?

The Poisson distribution is a limiting case of the binomial distribution when the number of trials is very large and the probability of success is very small. The Poisson distribution is used to model the number of occurrences of rare events in a fixed interval of time or space, while the binomial distribution is used to model the number of successful outcomes in a fixed number of trials.


Is binomial probability distribution always negatively skewed?

No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.No. It depends on the probability of success, p. If p < 0.5 the distribution is positively skewed.


What conditions must be met to use the normal distribution to approximate the binomial distribution?

To use the normal distribution to approximate the binomial distribution, the sample size must be sufficiently large, typically ensuring that both (np) and (n(1-p)) are greater than or equal to 5, where (n) is the number of trials and (p) is the probability of success. This ensures that the binomial distribution is not too skewed. Additionally, the trials should be independent, and the probability of success should remain constant across trials.