WGU C207 DATA DRIVEN DECISION MAKING FINAL EXAM 2026 WITH A
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EXPERT VERIFIED QUESTIONS AND ANSWERS FOR GUARANTEED PASS
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How would a greater number of samples and a fewer number of populations
affect an ANOVA analysis?
The results would be more accurate.
Mary is determining the likelihood that she will lose money on an investment.
There is an expected 10 percent gain in a normally distributed dataset, with a
standard deviation of 10 percent. The likelihood she'll lose money is _______
percent.
16
Select the choice that is true. Regression analysis:
takes information from one data set and can predict information for another data
set.
Jane works for a public health company. She is working on an anti-tobacco
campaign and is interested in how smoking cigarettes affects a smoker's
cholesterol. She could use the number of cigarettes smoked per day as her
_____ variable and place it on the __-axis. independent, x
We perform a regression analysis on a pair of variables and determine that there
is a linear relationship. The regression line is determined to be y=12x−5y=12x-5.
What type of linear relationship exists between the independent variable, x, and
the dependent variable, y?
positive describe R-squared?
R-squared measures the goodness of fit.
R-squared can be misleading if there are false independent variables.
R-squared is 1.0 when correlation is -1 or 1.
Which of the following are technique a manager uses when forecasting?
A)Time Series
Associative
,Judgmental
Which of the following are advantages of cluster analysis?
It sorts individual data points into different groups.
It will not help in determining target markets.
It does not identify successful and unsuccessful habits and systems.
A trend is...
a general slope upward or downward over a long period of time.
If there is a relationship between variables, but the relationship is not linear,
what possible challenge with regression could it be?
Polynomial Regression
Catherine is trying to sell a ticket to the Super Bowl. She is determining whether
or not she should sell a ticket now or wait until just before the game and try and
sell it then. Currently, someone is offering $350 for the ticket. From research of
past prices, she knows that the tickets immediately before the Super Bowl are
sold for about $500. She determines that there is a 75 percent chance she will
be able to sell the ticket immediately before the Super Bowl. Based on expected
payoffs from risk decision making, what should she do? How much is the
difference if she chooses to sell now
Catherine should wait to sell ticket; the difference will be $25.
Heteroscedasticity
A regression in which the variances in y for the values of x are not equal
Cumulative Average-Time Learning Model
A learning curve model in which the cumulative average time per unit declines
by a constant percentage each time the cumulative quantity of units produced is
doubled
Dependent Variable
The variable whose value depends on one or more variables in the equation;
typically the cost or activity to be predicted
Independent Variable
,The variable presumed to influence another variable (dependent variable);
typically it is the level of activity or cost driver
Analysis of Variance (ANOVA)
A statistical method that helps identify the sources of variability by comparing
their means or averages; it compares the variation within a sample to the
variation between samples to see if any differences are the result of some
contributing factor or if the differences occur by chance alon
Experience Curve
A curve that shows the decline in cost per unit in various business functions of
the value chain as the amount of these activities increases
Crossover Analysis
Allows a decision maker to identify the crossover point, which represents the
point at which we are indifferent between the plans
Cyclicality
Repetition of up (peaks) or down movements (troughs) that follow or counteract
a business cycle that can last several years
Linear Programming
A mathematical tool used to optimize a function (the objective function) subject
to various constraints, all of which are linear. Often used to find the combination
of products that will maximize profits or minimize costs
Simple Linear Regression
A form of regression analysis with only one independent variable Regression
Line
the "line of best fit" where the margin of error at every point is minimized
Data Management
The management, including cleaning and storage, of collected data
Random Variation
The variability of a process which might be caused by irregular fluctuations due
to chance that cannot be anticipated, detected, or eliminated
Seasonality
, Regular pattern of volatility, usually within a single year
Homoscedasticity
A regression in which the variances in y for the values of x are equal or close to
equal
Irregularity
One-time deviations from expectations caused by unforeseen circumstances
such as war, natural disasters, poor weather, labor strikes, single-occurrence
companyspecific surprises or macroeconomic shocks
Chi-squared Test
A hypothesis test that is used to examine the distribution of categorical data
Expected Value
The Expected Value for an alternative is the sum of all possible payoffs for that
alternative, each weighted by the probability of that payoff occurring
Multiple Linear Regression
A statistical method used to model the relationship between one dependent (or
response) variable and two or more independent (or explanatory) variables by
fitting a linear equation to observed data
Regression Analysis
A statistical analysis tool that quantifies the relationship between a dependent
variable and one or more independent variables
Decision Tree
A diagram of possible alternatives and their expected consequences used to
formulate possible courses of actions in order to make decisions
Time Series Analysis
Regression analysis that uses time as the independent variable
Expected Value
The Expected Value for an alternative is the sum of all possible payoffs for that
alternative, each weighted by the probability of that payoff occurring.
R-squared
STUDY GUIDE AND PRACTICE EXAM TEST BANK | ACCURATE AND
EXPERT VERIFIED QUESTIONS AND ANSWERS FOR GUARANTEED PASS
| GRADED A| INSTANT PDF DOWNLOAD
How would a greater number of samples and a fewer number of populations
affect an ANOVA analysis?
The results would be more accurate.
Mary is determining the likelihood that she will lose money on an investment.
There is an expected 10 percent gain in a normally distributed dataset, with a
standard deviation of 10 percent. The likelihood she'll lose money is _______
percent.
16
Select the choice that is true. Regression analysis:
takes information from one data set and can predict information for another data
set.
Jane works for a public health company. She is working on an anti-tobacco
campaign and is interested in how smoking cigarettes affects a smoker's
cholesterol. She could use the number of cigarettes smoked per day as her
_____ variable and place it on the __-axis. independent, x
We perform a regression analysis on a pair of variables and determine that there
is a linear relationship. The regression line is determined to be y=12x−5y=12x-5.
What type of linear relationship exists between the independent variable, x, and
the dependent variable, y?
positive describe R-squared?
R-squared measures the goodness of fit.
R-squared can be misleading if there are false independent variables.
R-squared is 1.0 when correlation is -1 or 1.
Which of the following are technique a manager uses when forecasting?
A)Time Series
Associative
,Judgmental
Which of the following are advantages of cluster analysis?
It sorts individual data points into different groups.
It will not help in determining target markets.
It does not identify successful and unsuccessful habits and systems.
A trend is...
a general slope upward or downward over a long period of time.
If there is a relationship between variables, but the relationship is not linear,
what possible challenge with regression could it be?
Polynomial Regression
Catherine is trying to sell a ticket to the Super Bowl. She is determining whether
or not she should sell a ticket now or wait until just before the game and try and
sell it then. Currently, someone is offering $350 for the ticket. From research of
past prices, she knows that the tickets immediately before the Super Bowl are
sold for about $500. She determines that there is a 75 percent chance she will
be able to sell the ticket immediately before the Super Bowl. Based on expected
payoffs from risk decision making, what should she do? How much is the
difference if she chooses to sell now
Catherine should wait to sell ticket; the difference will be $25.
Heteroscedasticity
A regression in which the variances in y for the values of x are not equal
Cumulative Average-Time Learning Model
A learning curve model in which the cumulative average time per unit declines
by a constant percentage each time the cumulative quantity of units produced is
doubled
Dependent Variable
The variable whose value depends on one or more variables in the equation;
typically the cost or activity to be predicted
Independent Variable
,The variable presumed to influence another variable (dependent variable);
typically it is the level of activity or cost driver
Analysis of Variance (ANOVA)
A statistical method that helps identify the sources of variability by comparing
their means or averages; it compares the variation within a sample to the
variation between samples to see if any differences are the result of some
contributing factor or if the differences occur by chance alon
Experience Curve
A curve that shows the decline in cost per unit in various business functions of
the value chain as the amount of these activities increases
Crossover Analysis
Allows a decision maker to identify the crossover point, which represents the
point at which we are indifferent between the plans
Cyclicality
Repetition of up (peaks) or down movements (troughs) that follow or counteract
a business cycle that can last several years
Linear Programming
A mathematical tool used to optimize a function (the objective function) subject
to various constraints, all of which are linear. Often used to find the combination
of products that will maximize profits or minimize costs
Simple Linear Regression
A form of regression analysis with only one independent variable Regression
Line
the "line of best fit" where the margin of error at every point is minimized
Data Management
The management, including cleaning and storage, of collected data
Random Variation
The variability of a process which might be caused by irregular fluctuations due
to chance that cannot be anticipated, detected, or eliminated
Seasonality
, Regular pattern of volatility, usually within a single year
Homoscedasticity
A regression in which the variances in y for the values of x are equal or close to
equal
Irregularity
One-time deviations from expectations caused by unforeseen circumstances
such as war, natural disasters, poor weather, labor strikes, single-occurrence
companyspecific surprises or macroeconomic shocks
Chi-squared Test
A hypothesis test that is used to examine the distribution of categorical data
Expected Value
The Expected Value for an alternative is the sum of all possible payoffs for that
alternative, each weighted by the probability of that payoff occurring
Multiple Linear Regression
A statistical method used to model the relationship between one dependent (or
response) variable and two or more independent (or explanatory) variables by
fitting a linear equation to observed data
Regression Analysis
A statistical analysis tool that quantifies the relationship between a dependent
variable and one or more independent variables
Decision Tree
A diagram of possible alternatives and their expected consequences used to
formulate possible courses of actions in order to make decisions
Time Series Analysis
Regression analysis that uses time as the independent variable
Expected Value
The Expected Value for an alternative is the sum of all possible payoffs for that
alternative, each weighted by the probability of that payoff occurring.
R-squared
