Gathering and Evaluating Information
What this domain tests
Candidates must judge whether information is relevant, reliable, and worth its cost. Key concepts: value of information (information is worth acquiring only if it could change the decision and its expected benefit exceeds its cost), selection bias (the sample is not representative), survivorship bias (only successes are observed), confirmation bias (seeking only supportive data), and base rates (prior frequencies should anchor estimates before case-specific detail).
Know the difference between correlation and causation, and the role of controlled comparison. Also know that more data is not always better: if the decision is robust across plausible values, extra precision adds cost without changing the choice.
Traps in questions
- Vivid anecdote over base rate: one dramatic case used to override a large sample.
- Survivorship: studying successful firms only and concluding a trait causes success.
- Precision as truth: a detailed forecast treated as more accurate than a simple one.
- Ignoring the cost of information: recommending more research without asking whether it could flip the decision.
Worked example
A retailer considers a new store. Current estimate: 60% chance of profit. A 20,000 survey would reveal demand, but the decision would change only in a narrow band of outcomes with probability 15%. Expected value of the survey is at most 0.15 times the value of switching decisions. If that is below 20,000, skip the survey and decide now. The test is whether the information can change the action, not whether it is interesting.
Rule of thumb
Before requesting more data, ask: "Could this change what we do?" If not, decide with what you have.