Statistics for Business Analytics Using MS Excel — Lesson 1: Business Data, Descriptive Statistics, and Visualization

Learning Objectives

• Prepare, clean, classify, and validate business data in Microsoft Excel
• Calculate central tendency, dispersion, percentiles, distributions, and descriptive summaries
• Create charts and analytical views that communicate patterns without misleading the audience

Detailed Topics

• Prepare: Prepare, clean, classify, and validate business data in Microsoft Excel
• Calculate central tendency: Calculate central tendency, dispersion, percentiles, distributions, and descriptive summaries
• Create charts and analytical views that communicate patterns without misleading the audience: Create charts and analytical views that communicate patterns without misleading the audience

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

Clean a business dataset and create an accurate descriptive-statistics dashboard.

• 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 Business Data, Descriptive Statistics, and Visualization in a realistic scenario and validate the result with documented evidence.