qmb quiz 2
________ probability requires that you count the frequency that an event occurs through an experiment and calculate the probability from the experiment's relative frequency distribution.
Empirical
A normal probability distribution's standard deviation (σ) completely describes its shape.
False
According to the Central Limit Theorem, if a distribution follows a bell-shaped, symmetrical curve centered around the mean, approximately 68, 95, and 99.7 percent of its values will fall within one, two, and three standard deviations above and below the mean respectively.
False
An exponential probability distribution allows us to calculate the probability of a specific number of successes for a certain number of trials.
False
If you are counting the number of customers visiting your store on a given day, you are working with continuous data.
False
The exponential probability distribution is a discrete distribution that is often used to describe time between customer arrivals.
False
The standard deviation of the continuous uniform distribution is equal to the mean of this distribution.
False
The addition rule is used to determine the probability of the intersection (joint probability) of two events occurring, or P(A and B).
False (Multiplication)
The probability of the intersection of two events is known as a ________ probability.
Joint
The mean and the variance are equal for a ________ probability distribution.
Poisson
________ probability represents the likelihood of a single event occurring by itself.
Simple
________ probability is used when we rely on experience and intuition to estimate the likelihood of an event.
Subjective
Which of the following is not a characteristic of a Poisson experiment?
The number of occurrences during one interval has to be dependent of the number of occurrences in any other interval.
Which of the following is not a characteristic of a binomial experiment?
The probability of a success must exceed the probability of a failure.
A listing of all the possible outcomes of an experiment for a discrete random variable along with the relative frequency of each outcome is called a discrete probability distribution.
True
Discrete random variables have outcomes that typically take on whole numbers as a result of conducting an experiment.
True
Testing whether a part is defective or not defective after it has been manufactured would be best described using a binomial probability distribution.
True
The area under the curve of the normal probability distribution is always equal to 1.0.
True
The complement to Event A is defined as all of the outcomes in the sample space that are not part of Event A.
True
The left and right ends of the normal probability distribution extend indefinitely, never quite touching the horizontal axis.
True
The number of typographical errors found in a manuscript would best be described using a Poisson probability distribution.
True
The z-score in a normal probability distribution determines the number of standard deviations that a particular value, x, is from the mean.
True
When two events are independent, the probability of them both occurring is simply the product of their individual probabilities of occurring.
True
With the continuous uniform probability distribution, the probability of any interval in the distribution is equal to any other interval with the same width.
True
A smaller standard deviation for the normal probability distribution results in
a skinnier curve that is tighter and taller around the mean.
Calculating the probability of drawing three aces with a random sample of five cards from a standard 52-card deck is using ________ probability.
classical
________ probability is used when we know the number of possible outcomes of the event of interest and the total number of possible outcomes in the sample space.
classical
When the discrete random variable is expressed in terms of dollars, the mean of the distribution is known as the ________________________.
expected monetary value
A discrete random variable that follows the Poisson distribution with a mean equal to λ has a counterpart continuous random variable that follows the ________ distribution with a mean equal to μ = 1/λ.
exponential
The ________ probability distribution is used to describe data where lower values tend to dominate and higher values don't occur very often.
exponential
An exponential probability distribution allows us to calculate the probability of a specific number of successes for a certain number of trials.
false
Continuous random variables have outcomes that typically take on whole numbers as a result of conducting an experiment.
false
The z-score follows a normal distribution with μ = 1 and σ = 0, which is known as the standard normal distribution.
false
The shape of the uniform probability distribution is ________.
flat
The ________of Events A and B represents the number of instances in which both Events A and B occur at the same time.
intersection
The ________ probability distribution is bell-shaped and symmetrical.
normal
The shape of the exponential distribution is ________.
right-skewed
The ________ of a discrete probability distribution measures the dispersion of each outcome of the random variable from the mean of the distribution.
standard deviation
At the beginning of a Major League Baseball season, a panel of sports writers decided that the Los Angeles Dodgers were the most likely team to win the World Series that year. This is an example of using ________ probability.
subjective
A probability is a numerical value that indicates the chance, or likelihood, of a specific event occurring.
true
An expected value is another term for the mean of a probability distribution.
true
If you are counting the number of customers visiting your store on a given day, you are working with discrete data.
true
Rating the satisfaction of a hotel room on a 1-5 scale is an example of a discrete random variable.
true
The mathematical expression that describes the shape of the curve for the exponential distribution is known as the exponential probability density function.
true
The ________ probability distribution describes data where all the values have the same chance of occurring.
uniform
Which of the following statements is true regarding z-scores for the normal probability distribution?
z-scores are negative for values of x that are less than the distribution mean.