Math for Business Operations

Applied Accounting with Excel

UNIT04 - Lesson 9

PBL Milestone 2: Prototype + Rehearsal

60 minutes (+20 min rehearsal & feedback)
Lesson Overview

Lesson Focus

Build working prototype, validate, rehearse; collect structured peer feedback

Key Unit Objectives

Enduring Understandings:

  • Data-driven decisions provide competitive advantages in business operations
  • Statistical analysis reveals patterns that guide inventory and staffing optimization
  • Forecasting models enable proactive business planning and risk management
  • Outlier identification prevents skewed analysis and faulty business conclusions

Lesson Activities

Activity 1: Prototype Build & Test
25 minutes

Implement forecast, validations, and test scenarios

Details:

  • Implement FORECAST.LINEAR or use Regression output
  • Add validations, IFERROR defaults, and audit flags
  • Run test scenarios; record results and change notes
Activity 2: Rehearsal Round 1
20 minutes

Deliver timed practice; collect peer feedback

Details:

  • 4–5 min timed delivery per team
  • Use PeerCritiqueForm categories aligned to rubric
  • Identify clarity gaps and data/visual issues
Activity 3: Incorporate Feedback
12 minutes

Refine model and narrative based on critique

Details:

  • Address validation flags and confusing visuals
  • Tighten storyline and transitions
  • Update test summary and change log
Activity 4: Quick Check
3 minutes

Confirm readiness for final presentations

Details:

  • All rubric areas addressed
  • Timing within 4–5 min window
  • Files named and organized for submission
Required Materials
  • PeerCritiqueForm and rubric reference
  • Test scenario worksheet
  • Audit panel checklist
  • Timing tools
Differentiation Strategies

For Struggling Students

  • • Guided Analysis Templates: Step-by-step worksheets for statistical calculations
  • • Simplified Datasets: Smaller, cleaner data samples for initial practice
  • • Visual Learning Supports: Screencasts demonstrating Analysis ToolPak procedures
  • • Peer Mentoring: Partner with students strong in statistical analysis
  • • Alternative Presentations: Poster session format instead of elevator pitch

For Advanced Students

  • • Multiple Regression Models: Explore relationships between multiple variables
  • • Seasonal Trend Analysis: Investigate more complex time-based patterns
  • • Statistical Significance Testing: Apply t-tests and confidence intervals
  • • Advanced Visualization: Create interactive dashboards or animated charts
  • • Consulting Role: Support other teams while completing their own analysis

For English Language Learners

  • • Statistical Vocabulary Support: Bilingual glossary of key terms with examples
  • • Visual Communication Emphasis: Focus on charts and infographics over verbal presentations
  • • Collaborative Team Roles: Pair with native speakers for presentation support
  • • Template-Based Writing: Structured formats for analysis documentation and reflection