MSIS 3223 Exam 2 Review Questions with solutions
classical definition of probability - -If the process that generates the outcome is known,
probabilities can be deduced from theoretical arguments, this is the ______
-Relative Frequency - -based on empirical data. The probability that an outcome will occur
is simply the relative frequency associated with that outcome.
-subjective definition of probability - -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 - -a numerical description of the outcome of an experiment
-discrete random variable - -when the number of possible outcomes can be counted
-continuous random variable - -has outcomes over one or more continuous intervals or
real numbers
-The ____ of a random variable corresponds to the notion of the mean or average for a
sample - -expected value
-Joint Probability - -the probability of the intersection of two events
-Conditional Probability - -the probability that one event happens given that another
event is already known to have happened
-How is the variance of a discrete random variable computed? - -as a weighted average of
the squared deviations from the expected value
-What does high variance mean in a random variable - -high uncertainty of the outcome
-Bernoulli Distribution - -The probability distribution of a random variable with two
possible outcomes, each with a constant probability of occurrence.
-Poisson distribution - -a discrete probability distribution describing the likelihood of a
particular number of independent events within a particular interval
-Normal Distribution - -a bell-shaped curve, describing the spread of a characteristic
throughout a population
-When does mean=median=mode? - -For normally distributed data
-What is the range of X in a normal distribution? - -it is unbounded, meaning that the tails
of the distribution extend to negative and positive infinity.
, -The empirical rules apply exactly for _______ - -Normal Distribution
-Probability density functions - -The distribution that characterizes outcomes of a
continuous random variable.
-Properties of Probability Density Functions: - -• A graph of the density function must lie
at or above the x-axis.
• The total area under the density function above the x-axis is 1.
• For continuous random variables, there are an infinite number of values.
• Calculates the probability of a random variable lying within a certain interval such as
between two numbers, or to the left or right of a number.
• P is the area under the density function between a and b.
-Regression Analysis - -tool for building mathematical and statistical models that
characterize relationships between a dependent variable (ratio) and one or more
independent, or explanatory, variables (ratio or categorical), all of which are numerical.
-Simple regression - -A regression model that involves a single independent variable
-Multiple Regression - -A regression model that involves two or more independent
variables
-What shows steady increase or decrease over the range of x and is the simplest type of
function used in predictive models? - -Linear Functions
-Logarithmic Functions - -are used when the rate of change in a variable increases or
decrease quickly and then levels out, such as diminishing returns to scale.
-Polynomial Function - -A second-order polynomial is parabolic in nature and has only
one hill or valley, a third-order polynomial has one or two hills or valleys. Revenue models
that incorporate price elasticity are often polynomial functions.
-________ have the property that y rises or falls at constantly increasing rates. - -Exponential
Functions
-_____ define phenomena that increase at a specific rate - -Power Functions
-R-Squared - -is a measure of the "fit" of the line to the data and will have a value between
0 and 1. The larger the value, the better the fit.
-Standard Error - -the variability of the observed Y-Values from the predicted values
-The more scattered the data, the ____ the error - -larger
classical definition of probability - -If the process that generates the outcome is known,
probabilities can be deduced from theoretical arguments, this is the ______
-Relative Frequency - -based on empirical data. The probability that an outcome will occur
is simply the relative frequency associated with that outcome.
-subjective definition of probability - -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 - -a numerical description of the outcome of an experiment
-discrete random variable - -when the number of possible outcomes can be counted
-continuous random variable - -has outcomes over one or more continuous intervals or
real numbers
-The ____ of a random variable corresponds to the notion of the mean or average for a
sample - -expected value
-Joint Probability - -the probability of the intersection of two events
-Conditional Probability - -the probability that one event happens given that another
event is already known to have happened
-How is the variance of a discrete random variable computed? - -as a weighted average of
the squared deviations from the expected value
-What does high variance mean in a random variable - -high uncertainty of the outcome
-Bernoulli Distribution - -The probability distribution of a random variable with two
possible outcomes, each with a constant probability of occurrence.
-Poisson distribution - -a discrete probability distribution describing the likelihood of a
particular number of independent events within a particular interval
-Normal Distribution - -a bell-shaped curve, describing the spread of a characteristic
throughout a population
-When does mean=median=mode? - -For normally distributed data
-What is the range of X in a normal distribution? - -it is unbounded, meaning that the tails
of the distribution extend to negative and positive infinity.
, -The empirical rules apply exactly for _______ - -Normal Distribution
-Probability density functions - -The distribution that characterizes outcomes of a
continuous random variable.
-Properties of Probability Density Functions: - -• A graph of the density function must lie
at or above the x-axis.
• The total area under the density function above the x-axis is 1.
• For continuous random variables, there are an infinite number of values.
• Calculates the probability of a random variable lying within a certain interval such as
between two numbers, or to the left or right of a number.
• P is the area under the density function between a and b.
-Regression Analysis - -tool for building mathematical and statistical models that
characterize relationships between a dependent variable (ratio) and one or more
independent, or explanatory, variables (ratio or categorical), all of which are numerical.
-Simple regression - -A regression model that involves a single independent variable
-Multiple Regression - -A regression model that involves two or more independent
variables
-What shows steady increase or decrease over the range of x and is the simplest type of
function used in predictive models? - -Linear Functions
-Logarithmic Functions - -are used when the rate of change in a variable increases or
decrease quickly and then levels out, such as diminishing returns to scale.
-Polynomial Function - -A second-order polynomial is parabolic in nature and has only
one hill or valley, a third-order polynomial has one or two hills or valleys. Revenue models
that incorporate price elasticity are often polynomial functions.
-________ have the property that y rises or falls at constantly increasing rates. - -Exponential
Functions
-_____ define phenomena that increase at a specific rate - -Power Functions
-R-Squared - -is a measure of the "fit" of the line to the data and will have a value between
0 and 1. The larger the value, the better the fit.
-Standard Error - -the variability of the observed Y-Values from the predicted values
-The more scattered the data, the ____ the error - -larger
