For each Bernoulli process, find the expected number of successes:
1. Number of trials =10, Probability of success =0.6
2. Number of trials =210, Probability of success =1/10.
3. Number of trials =43, Probability of success =0.3.
4. Number of trials =23, Probability of failure =0.8.
5. Number of trials =59, Probability of failure =2/7.
For each Bernoulli process, find the expected number of successes: 1. Number of trials =10, Probability...
Problem 1 Consider a sequence of n+m independent Bernoulli trials with probability of success p in each trial. Let N be the number of successes in the first n trials and let M be the number of successes in the remaining m trials. (a) Find the joint PMF of N and M, and the marginal PMFs of N and AM (b) Find the PMF for the total number of successes in the n +m trials.
Problem 1 Consider a sequence...
5A A Bernoulli Trials experiment consists of 4 trials, with a 4/5 probability of success on each trial. What is the probability of at least 1 success and at least 1 failure? What is the probability of 2 successes, given at least 1 success? What is the probability of at least 2 successes, given at least 2 failures? Enter your answers as whole numbers or fractions in lowest terms.
5c A Bernoulli Trials experiment has p=8/23 probability of success on each trial What is the expected number of successes in five trials? What is the expected number of failures in 14 trials? What is the expected number of failures in 46 trials?
a) Consider the following data on a variable that has Bernoulli distribution: X P (X) 0 0.3 1 0.7 Find the Expected value and the variance of X. And E(X)-X Px) b) Consider the following information for a binomial distribution: N number of trials or experiments 5 x- number of success 3 Probability of success p 0.4 and probability of failure 1-p 0.6 Find the probability of 3 successes out of 5 trials: Note P(x) Nox p* (1-p)Note: NcN!x! (N-x)!...
Problem 5 (10 points). Suppose that the independent Bernoulli trials each with success probability p, are performed independently until the first success occurs, Let Y be the number of trials that are failure. (1) Find the possible values of Y and the probability mass function of Y. (2) Use the relationship between Y and the random variable with a geometric distribution with parameter p to find E(Y) and Var(Y).
Negative Binomial experiment is based on sequences of Bernoulli trials with probability of success p. Let x+m be the number of trials to achieve m successes, and then x has a negative binomial distribution. In summary, negative binomial distribution has the following properties Each trial can result in just two possible outcomes. One is called a success and the other is called a failure. The trials are independent The probability of success, denoted by p, is the...
2. Suppose 4 Bernoulli trials, each with success probability p, are con ducted such that the outcomes of the 4 experiments pendent. Let the random variable X be the total number of successes over the 4 Bernoulli trials are mutually inde- (a) Write down the sample space for the experiment consisting of 4 Bernoulli trials (the sample space is all possible sequences of length 4 of successes and failures you may use the symbols S and F). (b) Give the...
Calculate each binomial probability: (a) Fewer than 5 successes in 10 trials with a 15 percent chance of success. (Round your answer to 4 decimal places.) Probability (b) At least 1 successe in 9 trials with a 20 percent chance of success. (Round your answer to 4 decimal places.) Probability (c) At most 11 successes in 19 trials with a 70 percent chance of success. (Round your answer to 4 decimal places.) Probability ...
Let the probability of success on a Bernoulli trial be 0.29. a. In six Bernoulli trials, what is the probability that there will be 5 failures? (Do not round intermediate calculations. Round your final answers to 4 decimal places.) b. In six Bernoulli trials, what is the probability that there will be more than the expected number of failures? (Do not round intermediate calculations. Round your final answers to 4 decimal places.)
7.75. Let us repeat Bernoulli trials with parameter 0 until k successes occur. If Y is the number of trials needed: (a) Show that the p.d.f. of Y is g(y; 0) Oyyk. k- k+1,..., zero elsewhere, where 0< es 1. (b) Prove that this family of probability density functions is complete. (c) Demonstrate that E[(k - 1)/(Y- 1)] 0 (d) Is it possible to find another statistic, which is a function of Y alone, that is unbiased? Why?
7.75. Let...