WGU C 207 Data Driven Decision Making Exam Questions And Answers, Complete Solution
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WGU C 207
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WGU C 207
WGU C 207 Data Driven Decision Making Exam Questions And Answers, Complete Solution
Blind Study
A study performed where the participants are not told if they are in the treatment group or control group
Interval Data
Data that is ordered within a range and with each data point being an equal in...
wgu c 207 data driven decision making exam questions and answers
complete solution blind study a study performed where the participants are not told if they are in the treatment group or control gro
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WGU C 207 Data Driven Decision Making
Exam Questions And Answers, Complete Solution
Blind Study
A study performed where the participants are not told if they are in the treatment group
or control group
Interval Data
Data that is ordered within a range and with each data point being an equal interval
apart
Reliable Data
Data that is consistent and repeatable
Systematic Errors
Errors in measurement that are constant within a data set, sometimes caused by faulty
equipment or bias
Triple Blind Study
A study performed where neither the treatment allocator nor the participant nor the
response gatherer knows which group the participant is in
Big Data
A catch-phrase that describes a massive volume of data that is so large that it's difficult
to process using traditional database and software techniques.
Ratio Data
Similar to interval data in that the data that is ordered within a range and with each data
point being an equal interval apart, also has a natural zero point which indicates none of
the given quality.
Statistics
The science that deals with the interpretation of numerical facts or data through theories
of probability. Also, the numerical facts or data themselves.
Nominal Data
Sometimes called categorical data or qualitative data, this data type is used to label
subjects or data by name
Discrete Data
Data that can only take on whole values and has clear boundaries
Informational Bias
A prejudice in the data that results when either the respondent or the interviewer has an
agenda and is not presenting impartial questions or responding with truly honest
responses, respectively
Data Management
The management, including cleaning and storage, of collected data.
Analytics
The discovery, analysis, and communication of meaningful patterns in data.
Ordinal Data
Data that places data objects into an order according to some quality with higher order
indicating more of that quality
Double-Blind Study
A study performed where neither the treatment allocator nor the participant knows which
group the participant is in
, Measurement Bias
A prejudice in the data that results when the sample is not representative of the
population being tested
Valid Data
Data resulting from a test that accurately measures what it is intended to measure
Davenport-Kim Three-Stage Model
A decision-making model developed by Thomas Davenport and Jinho Kim that consists
of three stages: framing the problem, solving the problem, and communicating results
Omission Error
An error because something (for example, data or survey response) is missing.
Continuous Data
Data that can lay along any point in a range of data
Random Errors
Errors in measurement caused by unpredictable statistical fluctuations
Relational Database
A database structured to recognize relations among stored items of information.
Benchmarks
Standards or points of reference for an industry or sector that can be used for
comparison and evaluation.
Data Set
A collection of related data records on a storage device.
3 Steps of Davenport-Kim Three-Stage Model
1. framing the problem
2. solving the problem
3. communicating results
1. framing the problem
-Broad Definition of Business Problem
-Review what has happened in the past
-Type of Analysis
-What Data and How to Collect
2. solving the problem
-Specific question to analyze
-Type of Data, data collection and data error
-Analysis technique and analysis
3. communicating results
-Presentation of analysis output
-Recommendation
4 Types of Analytics
1. Descriptive Analytics
2. Diagnostic Analytics
3. Predictive Analytics
4. Prescriptive Analytics
1. Descriptive Analytics
What happened? (hindsight)
2. Diagnostic Analytics
Why did it happen? (insight)
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