Y12W08WR Thinking in expected value

Design
The writing prompt

Take a specific current decision you’re facing and work through it using expected-value reasoning — explaining where the framework helps, where it breaks down, and what you actually decide.

1Retrieval check

Q1.What does Kahneman and Tversky’s research show about how people make most decisions?

  • AThey calculate expected value accurately
  • BThey use other criteria (vividness, familiarity, recent experience) rather than probability-weighted outcomes — expected-value thinking is unusual
  • CThey always choose the worst option
  • DDecisions are random

Q2.What’s the article’s counter-thread against pure EV reasoning?

  • AEV reasoning always works
  • BEV can be mis-applied by ignoring variance — two choices with the same EV can differ radically in whether you can survive the worst case
  • CEV has no applications
  • DProbability doesn’t exist
Show answer key

Q1 → B. They use other criteria (vividness, familiarity, recent experience) rather than probability-weighted outcomes — expected-value thinking is unusual.In repeated decisions, expected-value thinking reliably outperforms intuition; in one-off decisions, probability itself is uncertain.

Q2 → B. EV can be mis-applied by ignoring variance — two choices with the same EV can differ radically in whether you can survive the worst case.For one-off decisions, check whether you can survive the worst case before letting the EV calculation decide.

2Prompt deconstruction

Command verb
DESIGN — apply EV explicitly, then decide
Must reference
Kahneman and Tversky; the article’s caveats on one-off decisions and variance
Must include
possible outcomes, best-guess probabilities, the EV calculation, and a stress-test
Close with
a specific decision defended in light of both the calculation and the caveats

3Position nudge

Where on the range does your proposal sit?

Pole A
Pole B

Pole Alightly calculated (rough probabilities, quick EV)

Pole Bheavily stress-tested (variance analysis, worst-case survival check)

Commit to a specific point; defend it in your planner.

4Planner — design the thing, then the trade-offs

The decision
Named concretely, with the two or three options.
Outcomes and probabilities
For each option, the main outcomes and your best-guess probabilities.
The EV
The expected-value calculation for each option.
Where EV breaks down for this case
Uncertainty of the probabilities; variance; worst-case survival.
My decision
Specific choice, defended with both the calculation and the caveats.

5Sentence stems

  • My proposal is ___.
  • I am grounding this in [researcher]’s finding that ___.
  • The main trade-off is ___: this design gains ___ but loses ___.
  • The most predictable objection is ___, and my response is ___.
  • I would know it was working after [time] if ___.
  • What I am most likely to abandon is ___, so I will build in ___ to prevent that.

6Exemplar paragraph (not about this article)

(1) The decision I am working through is whether to take on a paid tutoring contract that runs through my mid-year exams. Option A (take it): a fairly certain earn of $600 across the block, with an uncertain 20–30% hit to exam-prep time. (2) Option B (decline it): no income from it, full prep time preserved. (3) I am grounding this in Kahneman and Tversky’s research showing that EV-style analysis beats intuition for repeated decisions and in the article’s caveats on one-off, high-variance cases. (4) The EV comparison roughly favours Option A if you weight the money at face value and the exam hit at around 1–2 marks; it favours Option B if the exam hit is 3+ marks. The main trade-off is that the probabilities on the exam hit are genuinely uncertain, and the article’s variance caveat applies here — the worst case for Option A is a meaningfully worse exam result, which is harder to undo than $600 is to forgo. (5) The most predictable objection is that I’m letting loss-aversion outvote a positive EV, and my response is that loss-aversion is a reasonable weighting here because the downside has a longer tail. (6) My decision is to decline the contract and propose to start one after exams — accepting a lower EV in exchange for lower variance.

What this paragraph does, move by move

  1. States the decision and the options concretely.
  2. Supplies rough probabilities and the EV.
  3. Names where EV breaks down for this case.
  4. Addresses the variance and survival issue.
  5. Owns that loss-aversion is shaping the decision.
  6. Lands a specific choice defended in context.