Q. The selling price of product is subtracted from purchasing price of product to calculate

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Q. The process in which the trials are statistically independent and each trial of event has only two outcomes is classified as

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Q. If the chances of success in a distribution are 0.68 and the number of values in distribution are 4 then the mean of Poisson probability distribution is

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Q. If the trial is repeated 6 times and the chances of success for desired outcome is 0.75 then the variance for negative probability distribution is

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Q. In the normal distribution, the z-score and z-statistic are classified as names of

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Q. If the value of failure in binomial probability distribution is 0.70 and success is 0.30 and the number of values in distribution are 7 then the moment coefficient of kurtosis is

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Q. The binomial probability distribution is classified as symmetric if

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Q. The type of distribution which is useful when the occurrences of events are constant is classified as

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Q. The probability of failure in binomial distribution is denoted by

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Q. The variance of binomial probability distribution is larger in value if

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Q. If the random samples are drawn without replacement and the population from which samples are drawn is infinite then the method which is not applicable is

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Q. The value which is used to measure the distance between mean and random variable x in terms of standard deviation is called

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Q. The type of probability distribution whose standard deviation is one and the mean is equal to zero is classified as

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Q. The symbol λ is used to represent

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

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Q. The probability distribution having shape of bell and in which the values of mean lies in center of probability distribution is classified as

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Q. The formula of calculating the variance for negative binomial distribution is

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Q. In the normal distribution, the normal curve becomes more wider and more flatter because of

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Q. The binomial probability distribution is classified as skewed to left if

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Q. If the μ is equal to 4 then the variance of exponential probability distribution is

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