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| Section | Weight | Objectives |
|---|---|---|
| Statistical Concepts & Descriptive Analytics | 25% | - Data visualization: charts, graphs, dashboards - Data types, measurement scales, sampling methods - Measures of central tendency, dispersion, distribution |
| Decision Models & Prescriptive Analytics | 15% | - Decision trees, payoff matrices, expected value - Quality & process improvement tools - Optimization, sensitivity analysis |
| Foundations of Data-Driven Decision Making | 20% | - Ethics, privacy, and data governance - Types of analytics: descriptive, predictive, prescriptive - Role of data in business decisions |
| Predictive Analytics & Regression | 20% | - Simple & multiple linear regression - Interpreting coefficients, R-squared, significance - Forecasting & trend analysis |
| Probability & Statistical Inference | 20% | - Probability rules, distributions, expected value - Correlation vs. causation - Hypothesis testing, p-values, confidence intervals |
A digital marketing manager wants to determine whether conversion rates from the company's latest email campaign are about the same as the industry average or significantly different. Which statistical concept should be used to measure the data set?
Correct Answer: B 🗳️
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A company runs a regression analysis to determine sales based on advertising expenditures, which can be shown in a linear equation as y = 2x + 25,000. The company plans to spend $20,000 on advertising.
Which sales figure should the company expect to generate based on the given equation?
Correct Answer: C 🗳️
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What is an appropriate management use of statistics?
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Which process is designed to proactively prevent a problem?
Correct Answer: D 🗳️
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Which type of analysis determines whether there was a significant difference in the average donor solicitation amount between three nonprofit hospital events?
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