If only one event may occur on any one trial, then the events are said to be

1. independent.

2. exhaustive.

3. mutually exclusive.

4. continuous.

New probabilities that have been found using Bayes’ Theorem are called

1. prior probabilities.

2. posterior probabilities.

3. Bayesian probabilities.

4. joint probabilities.

A measure of central tendency is

1. expected value.

2. variance.

3. standard deviation.

4. all of the above.

To compute the variance of a discrete random variable, you need to know

1. the variable’s possible values.

2. the expected value of the variable.

3. the probability of each possible value of the variable.

4. all of the above.

The square root of the variance is

1. the expected value.

2. the standard deviation.

3. the area under the normal curve.

4. all of the above.

Which of the following is an example of a discrete distribution?

1. the normal distribution

2. the exponential distribution

3. the Poisson distribution

4. the Z distribution

The total area under the curve for any continuous distribution must equal

1. 1.

2. 0.

3. 0.5.

4. none of the above.

Probabilities for all the possible values of a discrete random variable

1. may be greater than 1.

2. may be negative on some occasions.

3. must sum to 1.

4. are represented by the area underneath the curve.

In a standard normal distribution, the mean is equal to

1. 1.

2. 0.

3. the variance.

4. the standard deviation.

The probability of two or more independent events occurring is

1. the marginal probability.

2. the simple probability.

3. the conditional probability.

4. the joint probability.

5. all of the above.

In the normal distribution, 95.45% of the population lies within

1. 1 standard deviation of the mean.

2. 2 standard deviations of the mean.

3. 3 standard deviations of the mean.

4. 4 standard deviations of the mean.

If a normal distribution has a mean of 200 and a standard deviation of 10, 99.7% of the population falls within what range of values?

1. 170–230

2. 180–220

3. 190–210

4. 175–225

5. 170–220

If two events are mutually exclusive, then the probability of the intersection of these two events

1. is 0.

2. is 0.5.

3. is 1.0.

4. cannot be determined without more information.

If $P\left(A\right)=0.4$ and $P\left(B\right)=0.5$ and $P\left(A\text{ and }B\right)=0.2,$ then $P\left(B|A\right)=$

1. 0.80.

2. 0.50.

3. 0.10.

4. 0.40.

5. none of the above.

If $P\left(A\right)=0.4$ and $P\left(B\right)=0.5$ and $P\left(A\text{ and }B\right)=0.2,$ then $P\left(A\text{ or }B\right)=$

1. 0.7.

2. 0.9.

3. 1.1.

4. 0.2.

5. none of the above.