MSIS 3223 - Exam 2 (Chapters 5-9)
T/F: Probability is the likelihood that an outcome occurs. - -True.
-T/F: The union of two events contains all outcomes that belong to either the two events. -
-True.
-T/F: Conditional probability is the probability of occurrence of one event 'A' given that
another event 'B' is known to be true or has already occurred. - -True.
-T/F: A probability distribution is the characterization of the possible values that a random
variable may assume along with the probability of assuming these values. - -True.
-T/F: A random variable is a numerical description of the outcome of an experiment. - -
True.
-T/F: The expected value of a random variable corresponds to the notion of the median for
a sample. - -False.
-T/F: The normal distribution is a continuous distribution that is described by the familiar
bell-shaped curve and is perhaps the most important distribution used in statistics. - -True.
-T/F: The triangular distribution is defined by the three parameters: the mean, median,
and mode. - -False.
-T/F: Higher variance implies low uncertainty. - -False.
-T/F: In Normal Distributions, Mean = Median = Mode - -True.
-T/F: Excel's Trendline feature cannot be used in modeling trends which include time
variables. - -False.
-T/F: The standard error may be assumed to be large if the data are clustered close to the
regression line. - -False.
-T/F: A good regression model has the fewest number of explanatory variables providing
an adequate interpretation of the dependent variable. - -True.
-T/F: Regression analysis is a tool for building mathematical and statistical models that
characterize relationships between a dependent variable and one or more independent, or
explanatory, variables. - -True.
-T/F: Simple linear regression involves finding a linear relationship between one
independent variable, X, and one dependent variable, Y. - -True.
T/F: Probability is the likelihood that an outcome occurs. - -True.
-T/F: The union of two events contains all outcomes that belong to either the two events. -
-True.
-T/F: Conditional probability is the probability of occurrence of one event 'A' given that
another event 'B' is known to be true or has already occurred. - -True.
-T/F: A probability distribution is the characterization of the possible values that a random
variable may assume along with the probability of assuming these values. - -True.
-T/F: A random variable is a numerical description of the outcome of an experiment. - -
True.
-T/F: The expected value of a random variable corresponds to the notion of the median for
a sample. - -False.
-T/F: The normal distribution is a continuous distribution that is described by the familiar
bell-shaped curve and is perhaps the most important distribution used in statistics. - -True.
-T/F: The triangular distribution is defined by the three parameters: the mean, median,
and mode. - -False.
-T/F: Higher variance implies low uncertainty. - -False.
-T/F: In Normal Distributions, Mean = Median = Mode - -True.
-T/F: Excel's Trendline feature cannot be used in modeling trends which include time
variables. - -False.
-T/F: The standard error may be assumed to be large if the data are clustered close to the
regression line. - -False.
-T/F: A good regression model has the fewest number of explanatory variables providing
an adequate interpretation of the dependent variable. - -True.
-T/F: Regression analysis is a tool for building mathematical and statistical models that
characterize relationships between a dependent variable and one or more independent, or
explanatory, variables. - -True.
-T/F: Simple linear regression involves finding a linear relationship between one
independent variable, X, and one dependent variable, Y. - -True.
