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Major Purchase or Life Decision Analysis

Rubric scoring Has example

Think through a large decision systematically.

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Help me make a major decision with a weighted scoring approach and a reality check. Decision: [DECISION]. Options: [OPTIONS]. What matters to me and how much: [MY_PRIORITIES]. Constraints (money, time, location, family): [CONSTRAINTS]. Facts about each option: [FACTS].

Step 1: Turn my priorities into 6 to 8 criteria and propose weights adding up to 100; ask me to adjust them before scoring if the weights look wrong.
Step 2: Score each option from 1 to 5 on each criterion with a one-line reason using my facts only. Mark guesses with "guess" and unknowns with "?".
Step 3: Show the weighted totals in a table with the arithmetic, then show the totals if the unknowns scored 1 and then 5, to see whether the ranking is robust.
Step 4: Hidden costs and risks: total cost of ownership over [YEARS] years, reversibility (how hard is it to undo?), and the worst case for each option.
Step 5: Regret test: which option will I most likely regret not trying in 10 years, and which in 10 months?
Step 6: Questions I should answer before deciding, who to talk to, and a small experiment (a trial, a rental, a conversation) that reduces uncertainty.

Give a recommendation with a confidence level, and say what new information would change it. Remind me that I make the decision.

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Criteria and weights (sum 100): total cost 30, reliability 20, running costs 20, space 15, comfort 15.
Option | Cost | Reliability | Running | Space | Comfort | Weighted
Car A | 4 | 3 | 3 | 4 | 3 | 3.45
Car B | 2 | 5 | 4 | 3 | 4 | 3.45
Arithmetic: Car A = 0.30x4 + 0.20x3 + 0.20x3 + 0.15x4 + 0.15x3 = 1.2+0.6+0.6+0.6+0.45 = 3.45.
Tie: robustness test with unknown reliability scored 1 then 5 shows Car B wins if the reliability reports are true.
Hidden costs over 5 years, reversibility, worst case. Regret test: Car B in 10 years. Experiment: rent each for a weekend. Recommendation: Car B (medium confidence).

• decision-making
• purchase