Statistics for Business Analytics Using MS Excel — Lesson 3: Hypothesis Testing, Correlation, and Regression

Learning Objectives

• Formulate null and alternative hypotheses and choose appropriate statistical tests
• Interpret p-values, significance, practical impact, and common decision errors
• Use correlation and regression to examine relationships and generate defensible predictions

Detailed Topics

• Formulate null and alternative hypotheses and choose appropriate statistical tests: Formulate null and alternative hypotheses and choose appropriate statistical tests
• Interpret p-values: Interpret p-values, significance, practical impact, and common decision errors
• Use correlation and regression to examine relationships and generate defensible predictions: Use correlation and regression to examine relationships and generate defensible predictions

Guided Demonstration

1. Review the requirement, environment, dependencies, roles, risks, and expected outcome.
2. Demonstrate the relevant configuration, analysis, code, or administration workflow step by step.
3. Capture settings, outputs, logs, screenshots, calculations, or test evidence.
4. Compare the observed result with the stated acceptance criteria.

Hands-On Activity

Test a business hypothesis and build a regression model with interpretation notes.

• Document assumptions and the planned sequence before making changes.
• Complete the activity and preserve evidence of normal and exception behavior.
• Record issues, corrective actions, and reusable operational or development notes.

Troubleshooting Focus

• Separate symptoms from causes and collect evidence before applying a fix.
• Check configuration, permissions, data, dependencies, capacity, connectivity, and recent changes.
• Validate rollback, recovery, support ownership, and user or business impact.

Validation Checklist

• The requirement and expected outcome are clear.
• The selected configuration, design, query, code, or process is documented.
• Normal, boundary, failure, security, and operational conditions are reviewed.
• The result is supported by evidence and the next improvement is prioritized.

Lesson Outcome

Learners can explain and apply Hypothesis Testing, Correlation, and Regression in a realistic scenario and validate the result with documented evidence.