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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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Q: How do you get p in the binomial distribution?
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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.


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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


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You distribute the binomial.


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 is a binomial distribution?

The binomial distribution is one in which you have repeated trials of an experiment in which the outcomes of the experiment are independent, the probability of the outcome is constant.If there are n trials and the probability of "success" in each trail is p, then the probability of exactly r successes is (nCr)*p^r*(1-p)^(n-r) :where nCr = n!/[r!*(n-r)!]and n! = n*(n-1)*...*3*2*1


Can normal distribution be used if the data is not normal?

You can use a normal distribution to approximate a binomial distribution if conditions are met such as n*p and n*q is &gt; or = to 5 &amp; n &gt;30.


What is difference between skew binomial and symmetric binomial distribution?

The skew binomial distribution arises when the probability of a particular event is not a half.