Rectangular Distribution MCQs Test Online PDF Book Download

Rectangular distribution multiple choice questions (MCQs), rectangular distribution test prep for online learning with MBA degree certificate eCourses. Learn probability distributions multiple choice questions (MCQs), rectangular distribution quiz questions and answers. Career test on rectangular distribution, binomial distribution, standard normal probability distribution, discrete probability distributions test for online what is probability courses distance learning.

Learn probability distributions practice test MCQs: if value of m in beta distribution is 35 and value of n in beta distribution is 50 then expected value of random variable x in beta distribution is, for free online courses with options 0.411, 0.311, 0.511, 0.211 for business administration degree online. Free skills assessment test is for e-learning online rectangular distribution quiz questions for competitive assessment in business majors to prepare entrance exam for admission in top executive MBA programs.

MCQ on Rectangular DistributionQuiz Book Download

MCQ: Variance of random variable x of gamma distribution can be calculated as

  1. Var(x) = n + 2 ⁄ μsup2;
  2. Var(x) = n ⁄ μsup2;
  3. Var (x) = n * 2 ⁄ μsup2;
  4. Var(x) = n - 2 ⁄ μsup3;

B

MCQ: If value of m in beta distribution is 35 and value of n in beta distribution is 50 then expected value of random variable x in beta distribution is

  1. 0.411
  2. 0.311
  3. 0.511
  4. 0.211

A

MCQ: Formula of mean of uniform or rectangular distribution is as

  1. mean = 4(b + a) ⁄ 2b
  2. mean = (b + a) ⁄ 2
  3. mean = (b - 2a) ⁄ 4
  4. mean = (2a + 2b) ⁄ 2a

B

MCQ: Formula such as mn ⁄ (m + n)² (m + n + 1) is used to calculate

  1. variance in exponential distribution
  2. variance in alpha distribution
  3. variance in gamma distribution
  4. variance in beta distribution

D

MCQ: Formula of calculating expected value of random variable x of gamma distribution is as

  1. E(x) = n ⁄ μ
  2. E(x) = pq ⁄ μ
  3. E(x) = μ ⁄ np
  4. E(x) = α ⁄ μ

A