Probability analysis

In this lesson

1. 0:00 Probability analysis introduction
2. 1:24 Expected value concept and formula
3. 3:00 Calculating expected values worked example
4. 6:10 Joint probabilities and decision trees
5. 8:07 Multiple scenario analysis with probabilities
6. 10:16 Advantages and limitations of probability analysis

About this lesson

scenarios. You'll understand when expected values are useful for decision-making and their key limitations, particularly for one-off decisions. This is essential knowledge for FM, AFM, and risk management modules across ACCA and CIMA qualifications. The session starts with probability fundamentals—what it means, how to express it as percentages or decimals, and why probabilities must sum to 100% or 1.0. You'll then move into investment appraisal applications, where probability helps assess how likely different cash flows are to occur. The core technique is expected value: a probability-weighted average that represents the long-run average outcome. Through worked examples using maintenance cost scenarios, you'll see how to calculate expected values for individual periods and how to handle joint probabilities when events influence one another across multiple years. A key takeaway is that expected values don't represent actual outcomes—they're tools for decision-makers with a neutral risk attitude making repeated decisions. The lesson also covers important limitations: expected values are misleading for one-off decisions, and because they rely on estimated outcomes and estimated probabilities, they're only as reliable as your input data. By the end, you'll be confident applying probability analysis to investment decisions and understanding when this approach is—and isn't—appropriate.

Duration: 11m