Recipe
Test a candidate surprise function for additivity
Use when: you have a candidate function s(p) meant to measure information or surprise, and need to check whether it satisfies s(pq)=s(p)+s(q) for independent events
Goal: a definite pass or fail on the additivity requirement, using one concrete numeric pair as a fast screen
Taught in Why logarithms
Quick recipe
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1
Choose specific values for p and q, representing two independent events, keeping the arithmetic simple.
Example
p=0.25, q=0.5, testing the reciprocal candidate s(p)=\dfrac1p-1.
Why: additivity is a claim about every pair of probabilities, but a single well-chosen pair is enough to disprove it if it fails.
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2
Evaluate the candidate function separately at p and at q, then add the two results.
Example
s(0.25)+s(0.5) = \left(\dfrac{1}{0.25}-1\right)+\left(\dfrac{1}{0.5}-1\right) = 3+1 = 4.
Why: this is the value additivity claims the joint surprise should equal.
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3
Multiply p and q together first, then evaluate the candidate function at that single joint probability.
Example
pq=0.125, so s(0.125) = \dfrac{1}{0.125}-1 = 7.
Why: this is the value additivity is actually testing against, the surprise the candidate assigns to the combined event.
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4
Check whether the sum from Step 2 and the value from Step 3 come out equal.
Example
4 \neq 7: the reciprocal candidate fails additivity.
- the two results match — the candidate survives this particular test, though a genuine proof would still need to hold for every pair, not just one.
- the two results don't match — the candidate has definitively failed additivity, and no other requirement can rescue it.
Why: the two computed numbers not matching is a complete, immediate disproof; a single counterexample is all it takes to fail a claim that's supposed to hold for every pair.
Common mistakes
- Concluding a candidate passes additivity from one matching pair alone, without recognizing that's only a screen, not a full proof.
- Computing s(p) \cdot s(q) or s(p+q) instead of s(p)+s(q), testing the wrong algebraic combination entirely.
- Multiplying p and q incorrectly before evaluating s(pq), especially when the probabilities are already decimals.
- Assuming a candidate that passes every single-outcome requirement (decreasing, zero at certainty, unbounded) must automatically be additive too; additivity is a genuinely separate, pairwise check.