Negative binomial distribution is a particular of Geometric distribution for case r = 1. True False
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Q: The uniform Distribution is one discrete distributions صواب ihi
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Q: Negative binomial distribution is a particular of Geometric distribution for case r = 1. True O…
A:
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Q: Is this a binomial distribution? Explain.
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Q: When the binomial distribution is be used, dependent. the outcomes must ylgn ihi
A: Given,When the binomial distribution is used , the outcomesmust be dependent.
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- Question * The joint distribution of X and Y is given by: 3x²-2y f(x, y) For x = -1,0,2 and y = -1,0. Then P(Y = 0|X = 2) = 7/10 O 1/2 None of these 6/13How do you know when to use a specific distribution? For example, when would we use the Normal, binomial, grometric, hypergeometric, or negative binomial distribution? When doing so, when do we know if is is a discrete or continuous distribution?The exponintial distribution with λ = 7 is a special case of Gamma distribution when a=717,₁8=1 Option 2 a = 1,ß = 7 Option 3 a=1,8 = 1/
- Carect answers please fastWhich distribution(s) is/are symmetric? Select all that apply. Gamma Distribution Exponential Distribution Uniform Distribution Normal Distribution All of the above. None of the above.A binomial distribution has p = 0.35 and n = 100. If we are trying to approximate its probability using a normal approximation (applying the Central Limit Theorem) what is the standard deviation that we will use for this approximation? (a) 0.4770 (b) 0.2275 (c) 0.0477 (d) 4.7697 (e) None of the above
- for binomial distribution sample size 45 students and 35% get a grade in the class find out the probability that 20 students get a grade in the classa) Mean b) Binomial Distribution-(True or false) One of the Characteristic of a continuous random variables is “Probabilities are based on intervals, not on an individual value. -(True Or false) One of the Characteristics of the Normal Probability Distribution is “The distribution is bell-shaped and symmetrical around the variance.” (True or False) In Normal Probability Distribution, if µ increased, the curve will move to the left. (True or false) Any normal distribution (x) with mean µ and standard deviation σ can be transformed into the standard normal distribution (z) with µ=1 and σ =0