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Is binomial distribution is characterized by situations that are analogous to coin tossing?
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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 single parameter in the binomial distribution and what sample statistic would be used to estimate it?
The binomial distribution is defined by two parameters so there is not THE SINGLE parameter.
Consider a binomial distribution with 10 trials What is the expected value of this distribution if the probability of success on a single trial is 0.5?
Consider a binomial distribution with 10 trials What is the expected value of this distribution if the probability of success on a single trial is 0.5?
How many experimental outcomes are possible for the binomial and the Poisson distributions?
The binomial distribution is a discrete probability distribution. The number of possible outcomes depends on the number of possible successes in a given trial. For the Poisson distribution there are Infinitely many.
Is in binomial distribution mean always greater then variance?
yes
The binomial distribution is characterized by situations that are analogous to?
Rolling a six with a die or not rolling a six.
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.
What is difference between skew binomial and symmetric binomial distribution?
In a symmetric binomial distribution, the probabilities of success and failure are equal, resulting in a symmetric shape of the distribution. In a skewed binomial distribution, the probabilities of success and failure are not equal, leading to an asymmetric shape where the distribution is stretched towards one side.
Distinguish between binomial distribution and normal distribution?
Normal distribution is the continuous probability distribution defined by the probability density function. While the binomial distribution is discrete.
What is the relationship between the binomial expansion and binomial distribution?
First i will explain the binomial expansion
Why is it necessary to use a continuity correction when using a normal distribution to approximate a binomial distribution?
It is necessary to use a continuity correction when using a normal distribution to approximate a binomial distribution because the normal distribution contains real observations, while the binomial distribution contains integer observations.
Why is binomial distribution important?
Binomial distribution is the basis for the binomial test of statistical significance. It is frequently used to model the number of successes in a sequence of yes or no experiments.
What is the difference between poisson and binomial distribution?
Poisson and Binomial both the distribution are used for defining discrete events.You can tell that Poisson distribution is a subset of Binomial distribution. Binomial is the most preliminary distribution to encounter probability and statistical problems. On the other hand when any event occurs with a fixed time interval and having a fixed average rate then it is Poisson distribution.
What is the shape of the binomial probability distribution in rolling a die?
The distribution depends on what the variable is. If the key outcome is the number on the top of the die, the distribution in multinomial (6-valued), not binomial. If the key outcome is the number of primes, composite or neither, the distribution is trinomial. If the key outcome is the number of sixes, the distribution is binomial with unequal probabilities of success and failure. If the key outcome is odd or even the distribution is binomial with equal probabilities for the two outcomes. Thus, depending on the outcome of interest the distribution may or may not be binomial and, even when it is binomial, it can have different parameters and therefore different shapes.
For the normal distribution does it always require a continuity correction?
Use the continuity correction when using the normal distribution to approximate a binomial distribution to take into account the binomial is a discrete distribution and the normal distribution is continuous.
