BANA Exam 2

exponential probability distribution

A continuous probability distribution that is useful in describing the time, or space, between occurrences of an event is a(n)

expected value

A measure of the average value of a random variable is called a(n)

a standard normal distribution

A normal distribution with a mean of 0 and a standard deviation of 1 is called

random variable

A numerical description of the outcome of an experiment is called a

binomial probability distribution

A probability distribution showing the probability of x successes in n trials, where the probability of success does not change from trial to trial, is termed a

discrete random variable

An experiment consists of making 80 telephone calls in order to sell a particular insurance policy. The random variable in this experiment is a

50

Assume that you have a binomial experiment with p = 0.5 and a sample size of 100. The expected value of this distribution is

9

Assume your favorite football team has 2 games left to finish the season. The outcome of each game can be win, lose or tie. The number of possible outcomes is

the posterior probabilities

Bayes' theorem is used to compute

0.50

The assembly time for a product is uniformly distributed between 6 to 10 minutes. The probability of assembling the product between 7 to 9 minutes is

zero

The assembly time for a product is uniformly distributed between 6 to 10 minutes. The probability of assembling the product in less than 6 minutes is

combination

The counting rule that is used for counting the number of experimental outcomes when n objects are selected from a set of N objects where order of selection is not important is called

must always be equal to 0

The intersection of two mutually exclusive events

the probability of success changes from trial to trial

The key difference between the binomial and hypergeometric distribution is that with the hypergeometric distribution

0.25

The probability density function, f(x), for a uniform distribution ranging between 2 and 6 is

is equal to zero

The probability that a continuous random variable takes any specific value

is the mean of the distribution

The probability that a continuous random variable takes any specific value

the sample space

The set of all possible outcomes of an experiment is

all continuous probability distributions

The uniform, normal, and exponential distributions are

None of these alternatives is correct.

The union of two events with nonzero probabilities

squared deviations from the mean

The variance is a measure of dispersion or variability of a random variable. It is a weighted average of the

P(A)

if two events (A,B) are independent then the P(A|B) equals

0.25

Exhibit 5-11 A local bottling company has determined the number of machine breakdowns per month and their respective probabilities as shown below: Number of Breakdowns Probability 0 0.12 1 0.38 2 0.25 3 0.18 4 0.07 Refer to Exhibit 5-11. The probability of at least 3 breakdowns in a month is

0.017

Given that Z is a standard normal random variable, what is the probability that Z 2.12?

is 0.69

Given that event E has a probability of 0.31, the probability of the complement of event E

1/2

If a dime is tossed four times and comes up tails all four times, the probability of heads on the fifth trial is

one

If an experiment has n outcomes, the sum of the probabilities for each of the n outcomes must be equal to

0.50

In a standard normal distribution, the probability that Z is greater than zero is

Poisson distribution

In the textile industry, a manufacturer is interested in the number of blemishes or flaws occurring in each 100 feet of material. The probability distribution that has the greatest chance of applying to this situation is the

Σf(x) = 1 for all values of x

Which of the following is a required condition for a discrete probability function?