Binomial Poisson

The random variable, X has the binomial distribution X~B(9,0.25), find P(X=4)

• 0.1657

• 0.1168

• 0.2336

• 0.3504

The random variable Y has binomial distribution Y~B(10,0.4). Find P(3<Y<6)

• 0.6665

• 0.7779

• 0.4515

• 0.2508

The random variable T has binomial distribution T~(40,0.5). Find P(T≤12)

• 0.0032

• 0.0051

• 0.9968

• 0.0083

A ball manufacturer claims that only 15% of his balls are defective. If Ali has 6 of these balls to play with at a ball game, find the probability at most 4 balls will be defective.

• 0.9941

• 0.0059

• 0.9996

• 0.9527

A new surgical procedure is successful 85% of the time. the procedure is performed 8 times and it can be assumed that it is independent each time. Find the expected value of the successful operations.

• 1.02

• 6.8

• 0.1275

• 1.2

If X~Po(1.8), find P(2≤X≤4)

• 0.4285

• 0.7983

• 0.5008

• 0.7260

Salmi expected to receive 4 emails in a week. Find the probability of receiving 8 emails for the next 2 weeks.

• 0.0511

• 0.0297

• 0.5470

• 0.1395

A rental car service center company has 5 cars available for rental each day. Assume that each car is rented out for the whole day and that the number of cars rented out each day is randomly distributed with a mean of 2. Find the probability that the company cannot meet the demand for cars on any one day.

• 0.0166

• 0.0527

• 0.9473

• 0.0361

The article "Expectation Analysis of the Probability of Failure for Water Supply Pipes"† proposed using the Poisson distribution to model the number of failures in pipelines of various types. Suppose that for cast-iron pipe of a particular length, the expected number of failures is 1 (very close to one of the cases considered in the article). Then X, the number of failures, has a Poisson distribution with μ = 1. (Round your answers to three decimal places.)

(a) Obtain P(X =2)

The article "Expectation Analysis of the Probability of Failure for Water Supply Pipes"† proposed using the Poisson distribution to model the number of failures in pipelines of various types. Suppose that for cast-iron pipe of a particular length, the expected number of failures is 1 (very close to one of the cases considered in the article). Then X, the number of failures, has a Poisson distribution with μ = 1. (Round your answers to three decimal places.)

Determine P(2 ≤ X ≤ 4).