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No. If you keep track of all the numbers that are rolled then there are six possible outcomes, a binomial has only two. It is a multinomial distribution.

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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.

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No. It is multinomial because you have more than two possible outcomes each time.

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It is not.

There are only two possible outcomes for each toss of a coin whereas the number of possible outcomes when selecting a marble from a bag will depend on the numbers of distinct marbles in each bag.

The coin toss generates a binomial distribution the marbles experiment is multinomial.

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I will assume that you are asking about probability distribution functions. There are two types: discrete and continuous. Some might argue that a third type exists, which is a mix of discrete and continuous distributions.

When representing discrete random variables, the probability distribution is probability mass function or "pmf." For continuous distributions, the theoretical distribution is the probability density function or "pdf."

Some textbooks will call pmf's as discrete probability distributions.

Common pmf's are binomial, multinomial, uniform discrete and Poisson.

Common pdf's are the uniform, normal, log-normal, and exponential.

Two common pdf's used in sample size, hypothesis testing and confidence intervals are the "t distribution" and the chi-square. Finally, the F distribution is used in more advanced hypothesis testing and regression.

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multiterm mathematical expression: a mathematical expression consisting of the sum of a number of terms, each of which contains a constant and variables raised to a positive integral power

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Yes. When we refer to the normal distribution, we are referring to a probability distribution. When we specify the equation of a continuous distribution, such as the normal distribution, we refer to the equation as a probability density function.

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The Student's T- Distribution is a type of probability distribution that is theoretical and resembles a normal distribution. The Student T- Distribution differs from the normal distribution by its degrees of freedom.

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The Poisson distribution.



The Poisson distribution.



The Poisson distribution.



The Poisson distribution.

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Normal distribution is the continuous probability distribution defined by the probability density function. While the binomial distribution is discrete.

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The three types of spatial distribution are uniform distribution (evenly spaced), random distribution (no pattern), and clustered distribution (grouped together).

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The statement is true that a sampling distribution is a probability distribution for a statistic.

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le standard normal distribution is a normal distribution who has mean 0 and variance 1

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Personal income distribution and functional income distribution :)

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An unequal distribution of particles is called an asymmetrical distribution. :)

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Poisson distribution or geometric distribution

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No, it is the name given to the Gaussian distribution.

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When its probability distribution the standard normal distribution.

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The exponential distribution and the Poisson distribution.

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A sampling distribution refers to the distribution from which data relating to a population follows. Information about the sampling distribution plus other information about the population can be inferred by appropriate analysis of samples taken from a distribution.

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Intensive Distribution

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The special products include:

difference of the two same terms square of a binomial

cube of a binomial

square of a multinomial

(a+b) (a^2-ab+b^2)

(a-b) (a^2+ab+b^2)

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A bell shaped probability distribution curve is NOT necessarily a normal distribution.

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If the question is asking if a continuous distribution can be converted to a discrete distribution, the answer is yes.

Your age has a continuous distribution but in most cases, the information is recorded and analysed as if it were the whole number of years - a discrete distribution.

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The power distribution is a continuous distribution with a parameter that we will denote k.

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What is exclusive distribution and will you recommend exclusive

distribution for FMCGs?

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No it is a "discrete" distribution because the outcomes can only be integers.

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No, the normal distribution is strictly unimodal.

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The standard normal distribution is a normal distribution with mean 0 and variance 1.

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A binary distribution is a distribution of software using executable binaries, without source code, or another term for Bernoulli distribution.

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Exponential distribution is a function of probability theory and statistics. This kind of distribution deals with continuous probability distributions and is part of the continuous analogue of the geometric distribution in math.

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what is backward distribution

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Physical Distribution

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No, it is continuous.

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Monomial consisting of one term ( 3x ) , Binomial consisting of two terms ( x + y ), Trinomial consisting of three terms ( 3x+4x+5xy ), and Multinomial consisting of three or more terms.

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what is the history of distribution channels in Nigeria? what is the history of distribution channels in Nigeria?

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uneven distribution in farming is referring to the uneven distribution of rain fall

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discrete distribution is the distribution that can use the value of a whole number only while continuous distribution is the distribution that can assume any value between two numbers.

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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.

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It means distribution is flater then [than] a normal distribution and if kurtosis is positive[,] then it means that distribution is sharper then [than] a normal distribution. Normal (bell shape) distribution has zero kurtosis.

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The normal distribution and the t-distribution are both symmetric bell-shaped continuous probability distribution functions. The t-distribution has heavier tails: the probability of observations further from the mean is greater than for the normal distribution.

There are other differences in terms of when it is appropriate to use them.

Finally, the standard normal distribution is a special case of a normal distribution such that the mean is 0 and the standard deviation is 1.

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The definition of commercial distribution is USE Economic distribution. It is any distribution of human drugs with the exception of the use for investigational use. The term refers to distribution of devices meant for human use.

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what is the history of distribution channels in Nigeria? what is the history of distribution channels in Nigeria?

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