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OMBA 102 · Unit 3 of 7

Probability and Uncertainty

Data, Statistics and Managerial Decisions

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Learning objectives

After completing this unit, you will be able to:

  • Use probability as a language for uncertain business outcomes
  • Apply conditional probability and Bayes' rule to diagnostic problems
  • Recognize common probability distributions in operations and finance
  • Compute expected value and compare risky alternatives
  • Run spreadsheet simulations for managerial decisions

Why this matters

Managers choose under uncertainty every day: launches, hires, inventory, pricing. Unit 3 replaces gut feel with explicit probability thinking so you can compare bets, update beliefs with evidence, and communicate risk without false precision.

Unit overview

Work through the five lessons below in order. Use spreadsheet examples throughout.

#LessonCore idea
1Probability as a Language for UncertaintyEvents, odds, and coherence
2Conditional Probability and Bayes' RuleUpdating beliefs with new data
3Common Probability DistributionsNormal, binomial, Poisson intuition
4Expected Value and RiskEV, variance, and downside
5Simulation for Managerial DecisionsMonte Carlo thinking in Excel/Sheets

Connection to applied work

Model one uncertain decision for your project (demand, conversion, or cost) with a simple simulation or EV table. Record assumptions explicitly.

Practice

  1. Convert a business claim into a probability statement that could be wrong.
  2. Solve one Bayes problem (fraud, defect, or medical-style base rate).
  3. Match three business situations to plausible distributions.
  4. Compare two projects by expected value and worst-case outcome.

Knowledge check

  1. What is conditional probability in plain language?
  2. Why do base rates matter in Bayes problems?
  3. When is a normal approximation reasonable?
  4. When does expected value mislead?
  5. What does simulation add over point estimates?

Key takeaways

  • Probability forces explicit assumptions about uncertainty.
  • Updating with evidence is a core managerial skill.
  • Risk is more than average outcome.
  • Complete lessons before assessments.

Unit assessment

Complete each section below. Score 80%+ on the quiz to finish this unit's assessment.

40% applied project35% knowledge checks25% reflections

Exercises

Apply what you learned in this unit with structured practice.

ExerciseApplied practice: Probability and Uncertainty45 min
Complete a focused practice exercise on **Probability and Uncertainty**. 1. Choose a real company, product, or situation you know. 2. Apply one core framework from this unit to analyze it. 3. Write your analysis in 300–500 words with a clear recommendation. 4. Cite at least one credible source.

Deliverable

300–500 word analysis document saved to your portfolio under OMBA 102.

Rubric

  • • Framework applied correctly (not just named)
  • • Specific evidence from a real example
  • • Clear recommendation with tradeoffs acknowledged
  • • Professional writing with source citation
ExerciseDrill: Probability and Uncertainty30 min
Work through the practice problems in the unit lesson without looking at notes. Then check your work against the lesson and write a short reflection: - What you got right - One mistake you caught - One concept to review before the next unit

Deliverable

Problem solutions + 150-word reflection in your OMBA 102 workbook.

Rubric

  • • Attempted all practice items before checking answers
  • • Honest reflection on errors
  • • Identifies a specific review action

Model / spreadsheet

Build or extend a spreadsheet model tied to this unit.

ModelStructured model: Probability and Uncertainty60 min
Create a structured analytical model for **Probability and Uncertainty**. Document your assumptions, calculations, and conclusions in a format appropriate to OMBA 102 (diagram, table, or written model). Connect outputs to a decision a manager would make.

Deliverable

Structured model document (2+ pages) · One-paragraph summary of key insight from the model · Screenshot or export saved to portfolio

Rubric

  • • Assumptions stated explicitly
  • • Logic is auditable (formulas or steps visible)
  • • Output answers a specific business question
  • • Sensitivity or scenario considered

Knowledge quiz

Check your understanding before marking the unit complete.

1. P(demand is strong) = 0.55 and P(demand is weak) = 0.45. What must be true about these events in a standard probability model?

2. A screening test has 1% disease prevalence, 95% sensitivity, and 90% specificity. A positive result most strongly illustrates:

3. Which distribution is most appropriate for the number of defects in 200 inspected units with a stable defect rate?

4. For a symmetric normal distribution, approximately what share of values fall within one standard deviation of the mean?

5. Project A pays $100 with probability 0.6 and $40 with probability 0.4. What is the EMV?

6. Two investments have the same EMV. Investment 1 has a wide payoff spread; Investment 2 is nearly certain. A risk-averse manager likely prefers:

7. Monte Carlo simulation in a demand forecast primarily helps managers:

8. Treating macro demand and product demand shocks as independent when they move together in recessions will tend to:

Next unit: Statistical Inference →