Making a choice is easy; making the optimal choice under pressure is a science. Decision Theory is the backbone of strategic planning, whether you are a CEO deciding on a multi-million shilling investment or a researcher predicting environmental shifts. It provides a mathematical framework for evaluating risks, rewards, and the nagging uncertainty that comes with every “what if” scenario.
Below is the exam paper download link
PDF Past Paper On Decision Theory For Revision
Above is the exam paper download link
As the exam season approaches, the shift from reading about “Payoff Tables” to actually calculating the “Expected Value of Perfect Information” can be jarring. To ensure you aren’t caught off guard, we have broken down the core concepts into a digestible Q&A format, paired with a vital PDF past paper to anchor your revision.
Essential Decision Theory Questions and Answers
Q1: What is the main difference between ‘Decision Making under Risk’ and ‘Decision Making under Uncertainty’? The distinction lies in what you know about the future. Under Risk, you don’t know the exact outcome, but you have enough historical data or logic to assign probabilities (e.g., a 60% chance of rain). Under Uncertainty, you are flying blind—you know the possible outcomes, but you have no reliable way to assign odds to them. This is where criteria like Maximin and Maximax come into play.
Q2: How does the ‘Maximin’ criterion differ from the ‘Maximax’ approach? These represent two different psychological profiles. The Maximin approach is for the pessimist; it looks at the worst possible outcome for each decision and chooses the “best of the worst.” It’s about playing it safe. Conversely, Maximax is for the optimist; it identifies the highest possible payoff for each decision and picks the “best of the best,” ignoring potential losses.
Q3: Can you explain the concept of ‘Expected Opportunity Loss’ (EOL)? EOL is essentially a measure of “regret.” Instead of looking at how much money you made, it looks at how much more you could have made if you had known exactly what was going to happen. To calculate it, you subtract each payoff from the best possible payoff in that specific scenario. The goal is to choose the decision that minimizes this potential regret.
Q4: What exactly is a ‘Decision Tree’ and when is it most useful? A Decision Tree is a chronological map of a complex problem. It uses squares to represent “decision nodes” (where you choose) and circles to represent “chance nodes” (where nature or the market decides). It is most useful for sequential decisions—where your choice today depends on what happened yesterday and influences what you can do tomorrow.
Q5: What is the ‘Expected Value of Perfect Information’ (EVPI)? EVPI tells you the maximum amount of money you should be willing to pay for a “crystal ball.” It is the difference between the expected profit with perfect knowledge and the expected profit under current uncertainty. If a consultant charges 50,000 Kshs for a market report, but your EVPI is only 30,000 Kshs, the math tells you the report isn’t worth the investment.
The Power of Past Paper Revision
Theory provides the map, but past papers provide the terrain. Decision Theory exams are notorious for wordy case studies that try to hide the actual data you need.
By utilizing the PDF past paper linked below, you can:
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Master the Math: Practice drawing and “pruning” decision trees accurately.
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Identify Patterns: Examiners often use similar scenarios regarding manufacturing output or agricultural yields.
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Build Speed: Calculating payoffs and probabilities manually takes time; practicing under exam conditions ensures you don’t run out of minutes.
Access the Revision Material
Don’t leave your grades to chance. Click the link below to get your copy of the comprehensive revision paper.
Revision is about more than just reading notes; it’s about active problem-solving. Use this paper to challenge your assumptions and solidify your strategy. Good luck!
Last updated on: March 26, 2026