Data, Statistics and Managerial Decisions
Data literacy, descriptive statistics, probability, inference, and decision analysis for managers.
About this course
Data, Statistics and Managerial Decisions (OMBA 102) teaches you to use data as a manager, not as a statistician. You will learn to translate business questions into data questions, describe performance with the right summary measures, reason about uncertainty with probability, draw defensible conclusions from samples, model relationships and forecasts, and structure decisions when multiple outcomes and trade-offs are in play. The course closes with optimization and managerial modeling in spreadsheets so you can allocate resources and stress-test recommendations.
The emphasis is judgment under uncertainty. You will learn when a correlation is misleading, when a statistically significant result is not business-significant, and how to communicate analytical findings without drowning your audience in numbers.
Prerequisites: OMBA 101 recommended. Length: 4 weeks. Assessment: 40% applied project, 35% knowledge checks, 25% reflections.
What you will be able to do
By the end of OMBA 102, you should be able to:
- Frame business problems as testable data questions and assess data quality, missingness, and bias
- Summarize and visualize business performance with measures of center, dispersion, and distribution shape
- Use probability, expected value, and simulation to reason about risk and uncertainty
- Construct confidence intervals, run hypothesis tests, and distinguish statistical from business significance
- Build and interpret regression models while recognizing correlation limits and confounding
- Structure decisions with decision trees, sensitivity analysis, and linear programming (LP) in Excel or Google Sheets
How the course is organized
Seven units, 35 lessons. Work in order; later units assume foundations from earlier ones.
| Unit | Topic | Lessons | You will |
|---|---|---|---|
| 1 | Data Foundations | 5 | Translate business questions to data questions and assess quality, structure, and ethics |
| 2 | Describing Business Performance | 5 | Summarize distributions, visualize data, and build management dashboards |
| 3 | Probability and Uncertainty | 5 | Model uncertainty with probability, Bayes' rule, distributions, and simulation |
| 4 | Statistical Inference | 5 | Draw population conclusions from samples using intervals and hypothesis tests |
| 5 | Relationships and Prediction | 5 | Use correlation and regression for forecasting while spotting causality pitfalls |
| 6 | Decision Analysis | 5 | Build decision trees, run scenarios, and value information for managerial choices |
| 7 | Optimization and Managerial Modeling | 5 | Formulate and solve LP problems for resource allocation and product-mix decisions |
How to study
- Work with real datasets in spreadsheets. Replicate every calculation. Statistics is a doing skill; reading formulas without entering them will not stick.
- Always ask "so what for the business?" After every test or model, write one sentence on what a manager should do differently. Statistical significance without managerial significance is a common trap.
- Keep a running glossary. Define terms like p-value, confidence interval, R-squared, and feasible region in your own words as you encounter them.
- Complete unit assessments after all five lessons. Knowledge checks mix computation and interpretation. Reflections connect methods to decisions you face at work.
Applied work
Across OMBA 102 you will build portfolio pieces that compound:
- Applied project: End-to-end analysis of a business question from data framing through recommendation
- Case analysis: Decision memo using inference, regression, or decision-tree logic on a case dataset
- Portfolio artifact: Spreadsheet workbook with descriptive stats, a model, and documented assumptions
- Executive memo: Analytical recommendation with sensitivity analysis and clear limits of the evidence
What comes next
OPS 201: Operations and Process Management applies quantitative reasoning to process analysis, capacity, and planning. MKT 202: Customer Analytics and Market Research builds on inference and experimentation for marketing decisions. FIN 201: Corporate Finance and ACC 102: Managerial Accounting and Control also assume comfort with data-driven trade-off analysis. OMBA 102 is the quantitative backbone for analytical and management courses across the program.
Assessment
40% applied project, 35% knowledge checks, 25% reflections
Each unit includes a case component aligned to this weight.
Each unit includes a exercise component aligned to this weight.
Each unit includes a reflection component aligned to this weight.
Open any unit below to complete exercises, project tasks, and the knowledge quiz. Units auto-complete when all assessment items are submitted and you score 80%+ on the quiz.