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WGU C207 MODULES 1–6 EXAM REVIEW Q&A | COMPLETE STUDY GUIDE |

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Prepare for WGU C207 Data-Driven Decision Making with this comprehensive study guide covering Modules 1–6. Features practice questions and detailed answers designed to reinforce key concepts in descriptive and inferential statistics, probability, hypothesis testing, sampling methods, confidence intervals, regression analysis, data visualization, business analytics, research methods, and evidence-based decision-making. Ideal for WGU students preparing for module assessments, the Objective Assessment (OA), and overall course success.

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WGU C207 Modules 1 – 6 Exams Questions and
Verified Answers (100% Correct Answers)

Frame the Problem, Solving the Problem and Communicating Results are part of which decision making
model?

Davenport-Kim three-stage model




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

Framing the problem




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

Solving the problem




What is a key reason we study statistics?

To make informed decisions




Visually presenting the data assists in which stage of the Davenport-Kim model?

Communicating the results




When does research fail to produce reliable results?

Poor research validity




What are the two major issues surrounding research standards?

,Best practices and ethics




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

The appropriate size and random




Not selecting a random sample is what type of bias?

Measurement




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

Measurement




Research best practices eliminate...

Bias




Outliers create this type of error

Out-of Range




Unpredictable error

Random Error - No correlation




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

Omission Error - Distorted results

, This error repeats itself

Systematic Error - Skewed results




Observation points that are distant from other observations.

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




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

Measurement bias




Types of Bias: Bias introduced because respondents believe it will be beneficial if selected.

Conscious bias (key word: benefit)




Consistent and repeatable data

Reliable




Resulting from accurate measurements

Valid data




If a responder lies on their survey, this creates what type of bias?

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