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Probability Distributions
The discrete probability distribution in which the outcome is very small with a very small period of time is classified as
posterior distribution
cumulative distribution
normal distribution
Poisson distribution
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Probability Distributions
The type of probability distribution whose standard deviation is one and the mean is equal to zero is classified as
weighted probabilities distribution
standard normal probability distribution
normal cumulative probability distribution
approximated normal distribution
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Probability Distributions
If the value of interval a is 4 and the value of interval b is 5 then the variance of uniform distribution is
6.75
4.75
5.75
0.75
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Probability Distributions
The variance of random variable x of gamma distribution can be calculated as
Var(x) = n + 2 ⁄ μ²;
Var(x) = n ⁄ μ²;
Var (x) = n * 2 ⁄ μ²;
Var(x) = n – 2 ⁄ μ³;
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Probability Distributions
The successful life of product, the time, the weight and the height are classified as
continuous random variable
discrete random variable
continuous waiting time variable
continuous hyper geometric variable
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Probability Distributions
If the μ is equal to 4 then the variance of exponential probability distribution is
0.0625
0.085
0.0925
0.0725
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Probability Distributions
If the μ is equal to 25 then the value of mean for exponential probability distribution is
0.4
0.08
0.07
0.04
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Probability Distributions
The formula such as mn ⁄ (m + n)² (m + n + 1) is used to calculate
variance in exponential distribution
variance in alpha distribution
variance in gamma distribution
variance in beta distribution
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Probability Distributions
The mean of binomial probability distribution is 857.6 and the probability is 64% then the number of values of binomial distribution
1040
1340
1240
1140
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Probability Distributions
The probability which explains x is equal to or less than particular value is classified as
discrete probability
cumulative probability
marginal probability
continuous probability
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