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MSIS 3223 Exam 2 (Ch. 5, 8, 9) Correct Questions and Verified Answers

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it measures the uncertainty of a random variable. - ANSWER-Which of the following is true about variance? characterizes outcomes of a continuous random variable. - ANSWER-A probability density function: time-series - ANSWER-Regression models of ________ data focus on predicting the future. ...

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it measures the uncertainty of a random variable

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MSIS 3223 Exam 2 (Ch. 5, 8, 9) Correct Questions
and Verified Answers

it measures the uncertainty of a random variable. - ANSWER-Which of the following is
true about variance?

characterizes outcomes of a continuous random variable. - ANSWER-A probability
density function:

time-series - ANSWER-Regression 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. - ANSWER-The 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. -
ANSWER-Before launching a new line of toys, Toys Inc. used the method of historical
analogy to obtain a forecast. In this scenario, Toys Inc.:

classical - ANSWER-If the process that generates the outcome is known, probabilities
can be deduced from theoretical arguments; this is the _____ definition of probability.

relative frequency - ANSWER-The _____ 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 - ANSWER-The _____ 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 - ANSWER-A _____ is a numerical description of the outcome of an
experiment. They can be continuous or discrete.

discrete random variable - ANSWER-A _____ is a random variable for which the
number of possible outcomes can be counted.

continuous random variable - ANSWER-A _____ is a random variable that has
outcomes over one or more continuous intervals or real numbers.

expected value - ANSWER-The _____ 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 - ANSWER-The 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 - ANSWER-The probability distribution of a random variable with
two possible outcomes, each with a constant probability of occurrence is referred to as
_____.

Binomial Distribution - ANSWER-The _____ 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 - ANSWER-Perhaps the most important distribution used in
statistics, _____ is a continuous distribution by the familiar bell shaped curve.

mean and the standard deviation - ANSWER-Normal distribution is characterized by two
parameters: the _____ and the _____.

Zero - ANSWER-Normal distribution is symmetric, so its measure of skewness is
_____.

mean, median, mode - ANSWER-In normal distribution, the _____, _____, & _____ are
all equal. Thus, half the area falls above the mean and half falls below it.

unbounded - ANSWER-In normal distribution, the range of X is _____, meaning that the
tails of the distribution extend to negative & positive infinity.

empirical rules - ANSWER-In normal distribution, the _____ apply exactly for it.

probability density functions - ANSWER-The distribution that characterizes outcomes of
a continuous random variable.

x - ANSWER-Probability Density Functions:
A graph of the density function must lie at or above the _____-axis.

1 - ANSWER-Probability Density Functions:
The total area under the density function above the x-axis is _____.

continuous random variables - ANSWER-Probability Density Functions:
For _____, there are an infinite number of values.

probability - ANSWER-Probability Density Functions:

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