Sonus silentii fallacy
pud.com
pud.com
In this instance however, it'd be of the form, "if our product was defective, our customers would speak up. We haven't heard anything from our customers about it, therefore our product is not defective."
The author correctly points out that this formally follows the modus tollens format:
A: Our products are defective
B: Customers are complaining to us
P1. A → B
P2. ~B
------
C: ~A
However, it's important to point out that one can still inductively[3] conclude ~A is likely to be true, just not necessarily true. That is:
P1. Based on past evidence, our products being defective likely
means customers would speak up about it.
P2. Our customers haven't complained to us
-----
C: Our products are probably not defective.
[1]: https://en.wikipedia.org/wiki/Validity
It's called the problem of non-ignorable non-response.
Thank goodness for the internet...your app/device can report its own problems rather than waiting for your users to do it.
(BTW: MS product teams did quickly regroup to prioritize actual crash reports over the test lab.)
Which removes convenience, privacy, and resources from your users to make up for your shortage of proper design and testing.
/crank :)
Hell, the modus tollens is a valid argument form. If X, then Y. No Y, therefore no X (but this isn't strictly "evidence of absence").
And, no; absence of evidence is not evidence of absence. Absence of evidence is evidence of absence of evidence, and nothing more. "Whereof one cannot speak, thereof one must be silent."
EDIT: I'm speaking in terms of predicate logic here, not Bayesian logic. The absence of evidence proves nothing, though it can — and often does — indeed suggest something.
For "no evidence of X" to be no evidence against X, it would need to be true that you're no more likely to see evidence of X if X than if not-X. That's a pretty weird situation. It might happen if X were totally unobservable, or if you were being systematically deceived. (I would then say that nothing is evidence of X.) But the usual case is that evidence of X is more likely when X than when not-X, and then absence of evidence of X is evidence of not-X.
More formally: I take "A is evidence for B" to mean "Pr(B|A) > Pr(B)". "Absence of evidence is evidence of absence" means that if Pr(B|A) > Pr(B) then Pr(~B|~A) > Pr(~B). Assuming that none of the events involved is outright impossible, we can equivalently write the condition for being evidence as Pr(B|A) > Pr(B|~A), and the question is whether this implies Pr(~B|~A) > Pr(~B|A).
Well, we can express everything here in terms of four probabilities which I'll call AB, Ab, aB, ab. "Ab" means Pr(A & ~B), etc.: capital for true, lowercase for false. Now Pr(B|A) > Pr(B|~A) is AB/(AB+Ab) > aB/(aB+ab), and Pr(~B|~A) > Pr(~B|A) is ab/(aB+ab) > Ab/(AB+Ab).
The first, on clearing denominators, becomes AB(aB+ab) > aB(AB+Ab); a term AB.aB on each side cancels, leaving AB.ab > aB.Ab.
The second, on clearing denominators, becomes ab(AB+Ab) > Ab(aB+ab); a term ab.Ab on each side cancels, leaving ab.AB > Ab.aB.
And, lo and behold, these two conditions are the same. In other words, barring pathological cases where some of the probabilities are zero, "A is evidence for B" is exactly equivalent to "Not-A is evidence for not-B".
But the strength of the evidence can be very different in the two cases, as in Hempel's paradox: let A be "the object I just observed is a white crow" and B be "crows are not all black"; clearly A is very good evidence for B; so not-A is evidence for not-B; but if what you just observed is (say) a red car then it's very very weak evidence that all crows are black. But it's evidence, none the less: you just eliminated one possibility for something that might have been a counterexample.
Or, put another way: The real world isn't boolean. A and Not-A are not the only options; there's also "I don't know."
The last case there is what's generally referred to when people say that absence of evidence is not evidence of absence.
And here's where we need to distinguish knowledge of evidence from evidence itself; if you haven't collected any observations, then not knowing of any evidence doesn't imply that evidence is actually absent. In other words, "I don't know" isn't actually absence of evidence.
Of course, X usually is evidence of Y, and the above is far too high of standard anyway. Hence why I don't see fallacy guides as deeply insightful, nor any urgency in updating them to cover every special case.
In this case the manufacturer is in a position to have more evidence, at least in principle, even if they might be inclined to ignore it.
In my own experience, if Google didn't turn up other instances of my problem, the issue was extremely rare or caused by some unique quirk in my environment.
I corresponded with someone who works for the manufacturer. His response to me was (paraphrased), “we’ve sold thousands of these units and nobody else has complained. Therefore, our product must be good.”
I've never quite understood the logic behind this thinking on the part of product manufacturers. The product has already disappointed the customer on multiple occasions, but the customer is still willing to give the product another chance in the form of a repair or replacement; and the manufacturers first impulse is that rotten customer is stealing from us, treat him like some kind of thief.
They're about to lose that customer (and everyone he knows who asks him for a recommendation) forever. Send him a replacement. Send two. For bonus points, pay for him to ship the defective one back for detailed analysis of what was going wrong.
I did not catch his girlfriend's reaction, but I was disgusted. I'm sure Apple plans for and can afford this type of loyal customer, but everyone ends up paying for it.
For many companies, the rate of defects and replacements determines the difference between profit and bankruptcy.
* Our Internal Revenue Collection website must be really good, because no one ever complains about it, even though we have a conspicuous link to the complaints form on every page.
* Why would anyone ever hesitate to make a complaint to the Ministry of Internal Revenue Collection if they felt they had something to say?
If it's the former, then the story seems to miss the rather critical point that even if they were 100% certain that every other user was happy, that's irrelevant to whether he's got a faulty unit.
However good your quality control is, eventually a faulty one is going to fall through the net, so the fact that a thousand or a million other people have ones that didn't go wrong does't help the one person who's unit did.
Of course, if he claims to have had multiple faulty units, and no one else has ever reported any, that's a different matter.
edit: could also be labeled a non sequitur.
Underconstrained problem set: no $ figure, class of product, mfg name, or indication of who repaired it. Without any specifics, it's difficult to analyze the manufacturer's response in its true context.