OBA 311 midterm redone

The Poisson probability distribution is used with

a discrete random variable.

The binomial probability distribution is used with

a discrete random variable.

The uniform, normal, and exponential distributions

are all continuous probability distributions

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

binomial probability distribution

An exponential probability distribution

is a continuous distribution.

The mean of a standard normal probability distribution

is always equal to zero

The expected value for a binomial distribution is given by equation

np

For a uniform probability density function,

the height of the function is the same for each value of x.

normal probability distribution is

the most important distribution for describing a continuous random variable. - It is widely used in statistical inference - It has been used in a wide variety of applications including: Heights of people Amounts of rainfall, test scores

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

the probability of success changes from trial to trial

A uniform probability distribution is a continuous probability distribution where the probability that the random variable assumes a value in any interval of equal length is

the same for each interval

Which of the following is a required condition for a discrete probability function? a. ∑f(x) = 0 for all values of x b. f(x) 1 for all values of x c. f(x) < 0 for all values of x d. ∑f(x) = 1 for all values of x

∑f(x) = 1 for all values of x

Which of the following is not a characteristic of the normal probability distribution? a. Symmetry b. The total area under the curve is always equal to 1. c. 99.72% of the time the random variable assumes a value within plus or minus 1 standard deviation of its mean d. The mean is equal to the median, which is also equal to the mode.

99.72% of the time the random variable assumes a value within plus or minus 1 standard deviation of its mean

Uniform Probability Distribution is

A random variable is uniformly distributed whenever the probability is proportional to the interval's length.

Which of the following is a characteristic of an experiment where the binomial probability distribution is applicable? a. The experiment has at least two possible outcomes b. Exactly two outcomes are possible on each trial c. The trials are dependent on each other d. The probabilities of the outcomes changes from one trial

Exactly two outcomes are possible on each trial

The random variable x is the number of occurrences of an event over an interval of ten minutes. It can be assumed that the probability of an occurrence is the same in any two-time periods of an equal length. It is known that the mean number of occurrences in ten minutes is 5.3. Which of the following discrete probability distributions' properties are satisfied by random variable x?

Poisson

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

Poisson distribution.

If one wanted to find the probability of ten customer arrivals in an hour at a service station, one would generally use the

Poisson probability distribution

exponential probability distribution

The exponential probability distribution is useful in describing the time it takes to complete a task. The exponential random variables can be used to describe: Time between vehicle arrivals at a toll booth Time required to complete a questionnaire Distance between major defects in a highway

Which of the following is not a property of a binomial experiment? a. The experiment consists of a sequence of n identical trials b. Each outcome can be referred to as a success or a failure c. The probabilities of the two outcomes can change from one trial to the next d. The trials are independent

The probabilities of the two outcomes can change from one trial to the next

Continuous Probability Distributions:

The probability of the random variable assuming a value within some given interval from x1 to x2 is defined to be the area under the graph of the probability density function between x1 and x2.

The Poisson probability distribution is a

discrete probability distribution

The Poisson distribution:

provides an appropriate description of the number of occurrences per interval.