a Geometric random variable X has the cumulative distribution function as follows, what is its expectation? P(X ≤k) = 1-0.8k, k = 1,2,3,...
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- both subparts please 1 and 2 thank you!!SsCustomers arrive at a shop according to a Poisson process at a mean rate of 2 customers every ten minutes. The shop opens at 9am. (c) Let Y be the time (in hours) until the 4th customer arrives at the shop. State the distribution of Y and give the value(s) of its parameter(s). (d) Show that the probability of the time until the 4th customer arrives being greater than 15 minutes is 13e-3. (e) Let M be the number of customers who arrive at the shop between 9am and 12 noon. State the distribution of M and give the value(s) of its parameter(s). (f) Calculate P(M = 30) using a normal approximation with the continuity correction.
- Suppose that X follows a Binomial distribution, i.e., X ∼ Binomial(3, 0.5). Define a new random variable as Y = X 2 , then, what is the value of the PMF of Y evaluated at 1, i.e., what is Pr(Y=1)? a). 0.3125 b). 0.25 c). 0.375 d). 0.5Suppose X is a random variable of uniform distribution between 1 and 7. Find E(X)Suppose a random variable x is best described by a uniform probability distribution with range 0 to 5. Find the value of a that makes the following probability statements true.
- A random variable X is distributed as Poisson distribution with λ = 3.5. Usethis Poisson distribution (Table A.3) to determine the following probabilities: (a)P(X < 5), (b) P(2 ≤ X ≤ 6), (c) P(X > 7), (d) P(X ≥ 5).Person P is walking with his dog every day. He decides to model the time intervals between dog encounters (i.e., how long does it take between two encounters) with the independent random variables Y₁, . . ., Yn . Number of dogs encounters per day, the number of customers entering a store per hour, the number of bacteria per liter of water, etc. are classically modelled using the Poisson distribution. With an exponential distribution, on the other hand, is used for modelling intervals of between events and how long a light bulb lasts, for example. After learning this, person P decides to model the observations in such a way that the corresponding random variables Y1,..., Yn for a random sample, that is, independent observation, of the exponential distribution Exp(1/µ), µ > 0. The parameter µ > 0 is used as the statistical model parameter 1 which is the expected value of each observation random variable Yi. (a) Form the maximum likelihood estimate μ^(y) in the model for the parameter μ…A discrete random variable x has the the following probability distribution X 2 3 4 5 6 P(X=x) 3k2k2 3k2k2 3kk 2kk kk i) Find the value of k? ii) Find P[X>5][3.5<X<6.5]P[X>5][3.5<X<6.5]
- Suppose a random variable x is best described by a uniform probability distribution with a range 0 to 5. Find the value of a that makes the following probability statements true.True False? a)A sided dice with the probability of 1 and 6 coming p and the other numbers (2, 3, 4, 5) is 2p is rolled n times. x̄, is the average of the numbers in n shots. According to this information, p = 2 / 5x̄. b)If X1, ..., Xn, N is a random sample drawn from the distribution (μ, ϭ²), the sample mean x̄ and sample variance S² are always independent.
