BAN 001 Test 2 Practice No. 2

z is a standard normal random variable. The P (-1.20 z 1.50) equals a. 0.8181 b. 0.0483 c. 0.3849 d. 0.4332

a. 0.8181

A continuous random variable may assume a. any numerical value in an interval or collection of intervals. b. only the positive integer values in an interval. c. an infinite sequence of values. d. finite number of values in a collection of intervals.

a. any numerical value in an interval or collection of intervals.

The z score for the standard normal distribution a. can be either negative or positive. b. can never be negative. c. is always equal to the mean. d. is always equal to zero.

a. can be either negative or positive.

For any continuous random variable, the probability that the random variable takes a value less than zero a. is any number between zero and one. b. is more than one, since it is continuous. c. is a value larger than zero. d. is zero.

a. is any number between zero and one.

In a binomial experiment a. the probability does not change from trial to trial. b. the probability changes from trial to trial. c. the probability could change from trial to trial, depending on the situation under consideration. d. the probability could change depending on the number of outcomes.

a. the probability does not change from trial to trial.

Which of the following is a characteristic of the standard normal probability distribution? a. The mean, median, and the mode are not equal b. The standard deviation must be 1 c. The standard deviation must be 0 d. The distribution is not symmetrical

b. The standard deviation must be 1

Which of the following is not a characteristic of an experiment where the binomial probability distribution is applicable? a. The experiment has a sequence of n identical trials b. The trials are dependent c. Exactly two outcomes are possible on each trial d. The probabilities of the outcomes do not change from one trial to another

b. The trials are dependent

The Poisson probability distribution is used with a. any random variable. b. a discrete random variable. c. a continuous random variable. d. either a continuous or discrete random variable.

b. a discrete random variable.

The binomial probability distribution is used with a. a continuous random variable. b. a discrete random variable. c. a uniform random variable. d. an intermittent random variable.

b. a discrete random variable.

A standard normal distribution is a normal distribution with a. any mean and a standard deviation of 1. b. a mean of 0 and standard deviation of 1. c. a mean of 1 and a standard deviation of 1. d. a mean of 0 and a standard deviation of 0.

b. a mean of 0 and standard deviation of 1.

The standard deviation of a normal distribution a. is always 1. b. cannot be negative. c. can be any value. d. is always 0.

b. cannot be negative.

A description of the distribution of the values of a random variable and their associated probabilities is called a a. bivariate distribution. b. probability distribution. c. empirical discrete distribution. d. table of binomial probability.

b. probability distribution.

For a uniform probability density function, a. the height of the function is different for various values of x. b. the height of the function is the same for each value of x. c. the height of the function cannot be larger than one. d. the height of the function decreases as x increases.

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

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 a. different for each interval. b. the same for each interval. c. at least one. d. zero.

b. the same for each interval.

The probability that Pete will catch fish when he goes fishing is .8. Pete is going to fish 3 days next week. Define the random variable x to be the number of days Pete catches fish. The probability that Pete will catch fish on exactly one day is​ a. .008 b. .8 c. .096 d. .104

c. .096

The probability that Pete will catch fish when he goes fishing is .8. Pete is going to fish 3 days next week. Define the random variable x to be the number of days Pete catches fish. The probability that Pete will catch fish on one day or less is a. .096 b. .008 c. .104 d. .8

c. .104

x is a normally distributed random variable with a mean of 12 and a standard deviation of 3. The probability that x equals 19.62 is a. 0.4945 b. 0.9945 c. 0.000 d. 0.0055

c. 0.000

x is a normally distributed random variable with a mean of 5 and a variance of 4. The probability that x is greater than 10.52 is a. 0.9971 b. 0.4971 c. 0.0029 d. 0.0838

c. 0.0029

x is a normally distributed random variable with a mean of 22 and a standard deviation of 5. The probability that x is less than 9.7 is a. 0.000 b. 0.4931 c. 0.0069 d. 0.9931

c. 0.0069

z is a standard normal random variable. The P (1.41 < z < 2.85) equals a. 0.9185 b. 0.4207 c. 0.0771 d. 0.4978

c. 0.0771

z is a standard normal random variable. The P (1.20 ​ z 1.85) equals a. 0.8527 b. 0.4678 c. 0.0829 d. 0.3849

c. 0.0829

Which of the following is not a characteristic of the normal probability distribution? a. The mean of the distribution can be negative, zero, or positive b. The mean, median, and the mode are equal c. The standard deviation must be 1 d. The distribution is symmetrical

c. The standard deviation must be 1

The expected value of a discrete random variable a. is the most likely or highest probability value for the random variable. b. will always be one of the values x can take on, although it may not be the highest probability value for the random variable. c. is the average value for the random variable over many repeats of the experiment. d. is the value it is expected to assume in the next trial.

c. is the average value for the random variable over many repeats of the experiment.

For a continuous random variable x, the height of the function at x is a. 0.50, since it is the middle value. b. a value less than zero. c. named the probability density function f(x). d. the probability at a given value of x.

c. named the probability density function f(x).

For a normal distribution, a positive value of z indicates that a. all the observations must have had positive values. b. the sample mean is smaller than the population mean. c. the sample mean is larger than the population mean. d. the area corresponding to the z is either positive or negative.

c. the sample mean is larger than the population mean.

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) = 1 for all values of x d. f(x) 0 for all values of x

c. ∑f(x) = 1 for all values of x

For a standard normal distribution, the probability of z 0 is a. 1. b. -0.5. c. 0. d. 0.5.

d. 0.5.

The number of customers that enter a store during one day is an example of a. a continuous random variable. b. either a continuous or a discrete random variable, depending on whether odd or even number of the customers enter. c. either a continuous or a discrete random variable, depending on the gender of the customers. d. a discrete random variable.

d. a discrete random variable.

The Poisson probability distribution is a a. uniform probability distribution. b. normal probability distribution. c. continuous probability distribution. d. discrete probability distribution.

d. discrete probability distribution.

A measure of the average value of a random variable is called a(n) a. variance. b. standard deviation. c. coefficient of variation. d. expected value.

d. expected value.

The expected value for a binomial distribution is given by equation a. (n - 1)(1 - p). b. n(1 - p). c. (n - 1)p. d. np.

d. np.

A numerical description of the outcome of an experiment is called a a. descriptive statistic. b. probability function. c. variance. d. random variable.

d. random variable.

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

d. ∑f(x) = 1 for all values of x