it measures the uncertainty of a random variable. - ANSWERWhich of the following is true about variance?
characterizes outcomes of a continuous random variable. - ANSWERA probability density function:
time-series - ANSWERRegression models of ________ data focus on predicting the future.
us...
it measures the uncertainty of a random variable. - ANSWERWhich of the following is true about
variance?
characterizes outcomes of a continuous random variable. - ANSWERA probability density function:
time-series - ANSWERRegression models of ________ data focus on predicting the future.
uses a panel of experts, whose identities are typically kept confidential from one another, to respond
to a sequence of questionnaires. - ANSWERThe Delphi method used for forecasting:
noted the consumer response to similar previous products to marketing campaigns and used the
responses as a basis to predict how the new marketing campaign might fare. - ANSWERBefore
launching a new line of toys, Toys Inc. used the method of historical analogy to obtain a forecast. In
this scenario, Toys Inc.:
classical - ANSWERIf the process that generates the outcome is known, probabilities can be deduced
from theoretical arguments; this is the _____ definition of probability.
relative frequency - ANSWERThe _____ definition of probability is based on empirical data. The
probability that an outcome will occur is simply the relative frequency associated with that outcome.
subjective - ANSWERThe _____ definition of probability is based on judgment and experience as
sports experts might predict at the start of the football season—what is the probability of a specific
team winning the national championship?
Random variable - ANSWERA _____ is a numerical description of the outcome of an
experiment. They can be continuous or discrete.
discrete random variable - ANSWERA _____ is a random variable for which the number of possible
outcomes can be counted.
, Binomial Distribution - ANSWERThe _____ models n independent replications of a Bernoulli
experiment, each with a probability p of success. The _____ can assume different shapes and
amounts of skewness, depending on the parameters.
normal distribution - ANSWERPerhaps the most important distribution used in statistics, _____ is a
continuous distribution by the familiar bell shaped curve.
continuous random variable - ANSWERA _____ is a random variable that has outcomes over one or
more continuous intervals or real numbers.
expected value - ANSWERThe _____ of a random variable corresponds to the notion of the mean, or
average for a sample. It can be helpful in making a variety of decisions.
weighted average of the squared deviations - ANSWERThe variance of a discrete random variable
may be computed as a _____ from the expected value. A common measure of dispersion.
variance - ANSWER_____ is the average of the squared deviations of the observations from the
mean, a common measure of dispersion. It measures the uncertainty of the random variable; the
higher it is, the higher the uncertainty of the outcome.
Bernoulli Distribution - ANSWERThe probability distribution of a random variable with two possible
outcomes, each with a constant probability of occurrence is referred to as _____.
mean and the standard deviation - ANSWERNormal distribution is characterized by two parameters:
the _____ and the _____.
Zero - ANSWERNormal distribution is symmetric, so its measure of skewness is _____.
mean, median, mode - ANSWERIn normal distribution, the _____, _____, & _____ are all equal.
Thus, half the area falls above the mean and half falls below it.
unbounded - ANSWERIn normal distribution, the range of X is _____, meaning that the tails of the
distribution extend to negative & positive infinity.
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