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WGU C207 Decision Making Final Exam Study Guide & Key Concepts | Accurate & Verified Answers to Pass Actual Exam

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WGU C207 Decision Making Final Exam Study Guide & Key Concepts | Accurate & Verified Answers to Pass Actual Exam

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WGU C207 Decision Making Final Exam Study Guide & Key Concepts | Accurate & Verified

Answers to Pass Actual Exam


WGU C207 – Data-Driven Decision Making
COMPLETE OA MASTER STUDY GUIDE



1. What WGU C207 Tests (Read This First)

C207 does not test heavy math or software skills.
It tests your ability to:
• Identify the correct type of data
• Choose the appropriate analytical method
• Interpret results correctly
• Avoid false conclusions (especially causation errors)
• Support business decisions with data
You are being tested as a decision-maker, not a statistician.


2. Data-Driven Decision Making (Core Concept)

Data-Driven Decision Making
A structured approach to making business decisions by collecting, analyzing,
and interpreting data to reduce uncertainty and improve outcomes.
Key Goal
Use evidence—not intuition—to justify decisions.


3. Data vs. Information
Data
Raw facts or observations that have not yet been analyzed.
Information
Data that has been processed, organized, and interpreted to create meaning.


4. Data Types (Foundation of All Analysis)

Qualitative (Categorical) Data
Qualitative Data
Non-numerical data that describes characteristics or categories.

, Category
A group or label used to classify qualitative data.
Count
The total number of observations in a category.
Frequency
The number of times a category appears relative to the total number of
observations.
Mode
The category or value that occurs most frequently.
What qualitative data is used for
• Classification
• Comparison
• Pattern recognition
What it is NOT used for
• Averages
• Prediction equations


Quantitative (Numerical) Data
Quantitative Data
Numerical data that represents measurable or countable values.
Discrete Data

Whole, countable values (e.g., number of customers).
Continuous Data

Measured values that can take any value within a range (e.g., revenue,
time).


5. Measurement Scales (VERY HEAVILY TESTED)
Measurement Scale
Defines how data is measured and what analyses are valid.
Nominal Scale

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