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WGU Data-Driven-Decision-Making Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Probability & Statistical Inference	20%	- Correlation vs. causation - Hypothesis testing, p-values, confidence intervals - Probability rules, distributions, expected value
Topic 2: Predictive Analytics & Regression	20%	- Interpreting coefficients, R-squared, significance - Forecasting & trend analysis - Simple & multiple linear regression
Topic 3: Statistical Concepts & Descriptive Analytics	25%	- Data types, measurement scales, sampling methods - Data visualization: charts, graphs, dashboards - Measures of central tendency, dispersion, distribution
Topic 4: Decision Models & Prescriptive Analytics	15%	- Decision trees, payoff matrices, expected value - Optimization, sensitivity analysis - Quality & process improvement tools
Topic 5: Foundations of Data-Driven Decision Making	20%	- Ethics, privacy, and data governance - Role of data in business decisions - Types of analytics: descriptive, predictive, prescriptive

WGU VPC2Data-Driven Decision MakingC207 Sample Questions:

Question #1

An analyst used multiple linear regression to show how a big box store's sales (y) are predicted by the big box store's advertising expenditure in dollars (variable x1) and the advertising expenditure in dollars of a specialty store (variable x2) in the same market. The estimated regression is y = 651.57 + 92.30x1 # 26.89x2. How are advertising expenditures and sales related in this scenario?

A. If the big box store increases its advertising expenditures, its sales will decrease.
B. If the specialty store increases its advertising expenditures, it will decrease the big box store's sales.
C. If the big box store decreases its advertising expenditures, it will decrease the big box store's sales.
D. If the big box store decreases its advertising expenditures, its sales will increase.

Reveal Solution Discussion 0

Correct Answer: B 🗳️