Q. In binomial distribution, the formula of calculating mean is

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Q. The value which is obtained by multiplying the possible values of random variable with the probability of occurrence and is equal to weighted average is called

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Q. The number of products manufactured in a factory in a day are 3500 and the probability that some pieces are defected is 0.55 then the mean of binomial probability distribution is

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Q. If the value of interval a is 2.5 and the value of interval b is 3.5 then the value of mean for uniform distribution is

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Q. In binomial probability distribution, the success and failure generated by the trial is respectively denoted by

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Q. If the value of success in binomial probability distribution is 0.40 and failure is 0.60 and the number of values in distribution are 5 then the moment coefficient of skewness is

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Q. The class of variable which can accept any value within the upper and lower limit is classified as

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Q. If the value of x for normal distribution is 35, the mean of normal distribution is 65 and the standard deviation is 25 then the standardized random variable is

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Q. The formula of calculating mean for hyper geometric probability distribution is

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Q. The formula in which the binomial distribution approaches normal probability distribution with the help of normal variable is written as

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Q. If the value of m in beta distribution is 35 and the value of n in beta distribution is 50 then the expected value of random variable x in beta distribution is

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Q. In a negative binomial distribution of probability, the random variable is also classified as

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Q. The demand of products per day for three days are 21, 19, 22 units and their respective probabilities are 0.29, 0.40, 0.35. The profit per unit is $0.50 then the expected profits for three days are

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Q. The formula of mean of uniform or rectangular distribution is as

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Q. The normal distribution is also classified as

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Q. The probability which explains x is equal to or less than particular value is classified as

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Q. If the sample size is 6 and the population is 50 from which it is drawn without replacement and the elements for success are 22 then the variance of hyper geometric probability distribution is

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Q. The types of probability distributions by taking their functions of considerations must include

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Q. Consider the probability distribution as standard normal, if the value of μ is 75, the value of x is 120 with the unknown standard deviation of distribution then the value of z-statistic

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Q. If the value of p is 0.60 and value of n is 3 whereas the random variable x is equal to 4 then the value of z-score of distribution is

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