WGU C207 Data Driven Decision Making Module
1 Exam (Answered)
Quantitative analysis is another name for what?
statistics
If a dataset is presented on a scale of hours per week, which measurement scale
is used?
ratio
The use of data, statistical and quantitative analysis, explanatory and predictive
models, and fact-based management to drive decisions and add value is called
________.
Analytics
Analytics makes use of all these things to drive decision-making and add value.
First, second, third, fourth... What kind of data does this represent?
Ordinal data
Ordinal data places data objects into an ordered list according to some quality.
This kind of data is also called categorical data.
Nominal data
Nominal data is used to put data into categories, which is why it is also known as
categorical data.
Assume you are measuring the various lengths of used pencils, and you collect
the following data points (in inches): 1.37, 2.65, 2.78, 3.46, 3.91. What kind of data
are these data points?
continuous data
In a set of continuous data, a point can lay along with any point in a range of data.
A data point that can only take on whole values and has boundaries is called
what?
discrete
Discrete data points are always whole integers.
If a measure is consistent and repeatable it is said to be __________.
reliable
A measure must be repeatable in multiple locations under diverse conditions to be
considered reliable.
A small group from which you make an inference about an entire population is
called a __________.
sample
If chosen properly, a sample can make predictions about an entire population.
Cleaning and organizing data that has been collected is known as __________.
data management
Managing your data is as important as your analysis.
The first step in the Davenport-Kim three-stage model is to frame the problem by
recognizing what the problem is and then reviewing previous findings to begin to
structure the analysis. (t/f)
, (True) Stage # 1 is to frame the problem by recognizing what the problem is and then
reviewing previous findings to begin to structure the analysis. Stage #2 is to solve the
problem. Stage #3 is to communicate your findings.
The stage that involves the most intense statistics and data work is stage 3,
which involves communicating results. True or false?
False: The stage that involves the most intense statistics and data work is stage 2,
which solves the problem. Stage 2 includes data modeling, data collection, and data
analysis.
The following are examples of nominal data: T/F
male/female
red/blue
living/deceased
True: Nominal data, also called categorical data, places objects into a category.
Interval data has an order and all the objects are an equal interval apart. T/F
True. Interval data has an order, and all the objects are an equal interval apart. You can
not have a natural zero point in interval data.
Observational studies are often used when a surveyor wants to adjust different
variables and take note of the effects. T/F
False. Observational studies are used when it is impractical or impossible to control the
conditions of the experiment.
Data is valid if it can be repeated by the same person in the same lab each and
every time the experiment is executed. T/F
F. Data is only valid if more than one individual can execute the experiments in different
locations (different conditions are not required; this is part of the experiment ).
Big Data
a massive amount of data that is difficult to analyze using typical database and software
techniques.
Blind Study
A study performed where the participants are not told if they are in the treatment group
or control group.
Continuous Data
Data that can lie at any point in a range of data
Data Management
Cleaning and storage, of collected data
Decision Tree Analysis
The diagramming of possible alternatives and their expected consequences to
formulate possible courses of action to make decisions.
Discrete Data
Data that can only take on whole values and has clear boundaries.
Double-Blind Study
A study was performed where neither the treatment allocator nor the participant knew
which group the participant is in
Expected Monetary Value (EMV) Analysis
A statistical technique that calculates the average outcome when the future includes
scenarios that may or may not happen
Information Bias
1 Exam (Answered)
Quantitative analysis is another name for what?
statistics
If a dataset is presented on a scale of hours per week, which measurement scale
is used?
ratio
The use of data, statistical and quantitative analysis, explanatory and predictive
models, and fact-based management to drive decisions and add value is called
________.
Analytics
Analytics makes use of all these things to drive decision-making and add value.
First, second, third, fourth... What kind of data does this represent?
Ordinal data
Ordinal data places data objects into an ordered list according to some quality.
This kind of data is also called categorical data.
Nominal data
Nominal data is used to put data into categories, which is why it is also known as
categorical data.
Assume you are measuring the various lengths of used pencils, and you collect
the following data points (in inches): 1.37, 2.65, 2.78, 3.46, 3.91. What kind of data
are these data points?
continuous data
In a set of continuous data, a point can lay along with any point in a range of data.
A data point that can only take on whole values and has boundaries is called
what?
discrete
Discrete data points are always whole integers.
If a measure is consistent and repeatable it is said to be __________.
reliable
A measure must be repeatable in multiple locations under diverse conditions to be
considered reliable.
A small group from which you make an inference about an entire population is
called a __________.
sample
If chosen properly, a sample can make predictions about an entire population.
Cleaning and organizing data that has been collected is known as __________.
data management
Managing your data is as important as your analysis.
The first step in the Davenport-Kim three-stage model is to frame the problem by
recognizing what the problem is and then reviewing previous findings to begin to
structure the analysis. (t/f)
, (True) Stage # 1 is to frame the problem by recognizing what the problem is and then
reviewing previous findings to begin to structure the analysis. Stage #2 is to solve the
problem. Stage #3 is to communicate your findings.
The stage that involves the most intense statistics and data work is stage 3,
which involves communicating results. True or false?
False: The stage that involves the most intense statistics and data work is stage 2,
which solves the problem. Stage 2 includes data modeling, data collection, and data
analysis.
The following are examples of nominal data: T/F
male/female
red/blue
living/deceased
True: Nominal data, also called categorical data, places objects into a category.
Interval data has an order and all the objects are an equal interval apart. T/F
True. Interval data has an order, and all the objects are an equal interval apart. You can
not have a natural zero point in interval data.
Observational studies are often used when a surveyor wants to adjust different
variables and take note of the effects. T/F
False. Observational studies are used when it is impractical or impossible to control the
conditions of the experiment.
Data is valid if it can be repeated by the same person in the same lab each and
every time the experiment is executed. T/F
F. Data is only valid if more than one individual can execute the experiments in different
locations (different conditions are not required; this is part of the experiment ).
Big Data
a massive amount of data that is difficult to analyze using typical database and software
techniques.
Blind Study
A study performed where the participants are not told if they are in the treatment group
or control group.
Continuous Data
Data that can lie at any point in a range of data
Data Management
Cleaning and storage, of collected data
Decision Tree Analysis
The diagramming of possible alternatives and their expected consequences to
formulate possible courses of action to make decisions.
Discrete Data
Data that can only take on whole values and has clear boundaries.
Double-Blind Study
A study was performed where neither the treatment allocator nor the participant knew
which group the participant is in
Expected Monetary Value (EMV) Analysis
A statistical technique that calculates the average outcome when the future includes
scenarios that may or may not happen
Information Bias
