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WGU C207 Data Driven Decision Making Module 5 Questions and Answers Latest Update 2025–2026

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This document contains the latest set of questions and correct answers for Module 5 of WGU C207 Data Driven Decision Making. It covers key topics such as hypothesis testing, regression analysis, and data-driven decision models, providing detailed solutions to support effective learning. The material is structured to reinforce understanding and prepare students for assessments within this module.

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WGU C207 Data Driven Decision Making
Questions and Correct Answers/ Latest
Update / Already Graded
Frame the Problem, Solving the Problem and Communicating Results

are part of which decision making model?


Ans: Davenport-Kim three-stage model




In which stage of the Davenport-Kim model is problem recognition?


Ans: Framing the problem




In which stage of the Davenport-Kim model is data collection?


Ans: Solving the problem




What is a key reason we study statistics?


Ans: To make informed decisions

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Visually presenting the data assists in which stage of the Davenport-

Kim model?


Ans: Communicating the results




When does research fail to produce reliable results?


Ans: Poor research validity




What are the two major issues surrounding research standards?


Ans: Best practices and ethics




In order to be a statistically valid sample, the sample must be:


Ans: The appropriate size and random




Not selecting a random sample is what type of bias?


Ans: Measurement

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Not selecting a right sized sample is what type of bias?


Ans: Measurement




Research best practices eliminate...


Ans: Bias




Outliers create this type of error


Ans: Out-of Range




Unpredictable error


Ans: Random Error - No correlation




Error may occur from missing data. (Example: Space not filled in)


Ans: Omission Error - Distorted results




This error repeats itself

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Ans: Systematic Error - Skewed results




Observation points that are distant from other observations.


Ans: Outliers Note: Can be included or excluded in analysis (causes

skewness)




Types of Bias: Bias that occurs from not selecting a random sample


Ans: Measurement bias




Types of Bias: Bias introduced because respondents believe it will be

beneficial if selected.


Ans: Conscious bias (key word: benefit)




Consistent and repeatable data


Ans: Reliable




Resulting from accurate measurements

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