(Roberts), proffesor- - ( -, Kim)

Why did I make this proof

People quite often state wrongly that "Absence of evidence is NOT evidence of absence." Why do they do that? Perhaps because they do not know better? And with this proof they get the possibility of knowing for sure that"Absence of evidence IS evidence of absence.", which is quite useful in many situations, such as these:

Absence of evidence for...

  • ...fairies, trolls, and ghosts...
  • ...weapons of mass destruction in Iraq...
  • ...crop circle aliens...
  • ...gods...
  • ...Microsoft patents in Linux...
  • ...miracle healings...
  • ...credentials...
  • ...CO2 from machines causing global warming...
  • ...UFO space ships...
  • ...telepaty, ESP, and telekinesis...
  • ...Linux stealing code from SCO corporation...

...means they get less likely all the time.


    This is the reason why faith is bad.
    Faith is the assumption of truth when evidence is absent. This absence of evidence is evidence of absence of truth.
    So faith in itself is evidence of falseness.
    Therefore, faith is not a road to truth, but instead a road to falseness.
    , - . .

Carl Sagan is often quoted as saying "Absence of evidence is not evidence of absence", but he meant it as an example of what fools mean, and has since been consistently misquoted as something he meant.
Correct quote by Wikiquote.
Misquote by Quotationspage.

One source of this confusion may be that "evidence" is a near synonym to both "proof" and "sign/indication" which are two different concepts. Using these words instead gives the two following correct sentences: 

More serious is the American Statistical Association, who even sells a T-shirt with the wrong slogan on it. Being statisticians, they really should know better. Considering the large number of members who could have pointed out this error, it is rather telling that it is still there.

There was a previous version of this proof, but this new one is much shorter, simpler, and it also defines the concept of evidence, which is also very useful and absolutely necessary to understand what the proof is about, which many never did understand.

I have seen that the comprehension of this "absence of evidence" concept is one of the main differences between sensible and gullible people. Gullible people will not and cannot understand this concept.

A less proofy explanation:

For those of you who have not learned Bayesian inference yet, here is an explanation with words, examples, and analogies:

More women than men wear skirts. 
Both women and men can use trousers instead of skirts. 
Skirts for men are kalled kilts, and are usual in Scotland. 
Thus there are 4 possibilites:




a skirt




a skirt




a skirt




a skirt

A skirt is evidence of a woman, because there are more women than men wearing skirts.

So, if you see someone NOT wearing a skirt, then it is more likely a man.

Lastly, an anecdote from Roar Lauritzsen about Absence of Evidence:

"Suppose you are a programmer, and you are looking for bugs in a program. At first you cannot sleep at night because you are convinced that there must be a bug somewhere, you just haven't found it yet. To find the bug, you test the program to see if you find something that doesn't work as you expected. If you found something, it would be evidence that there was a bug. If you test the program a lot, and still find no evidence of a bug, this increases your confidence that there is no bug. In other words, it counts as evidence for the absence of a bug, and you are finally able to sleep better.

After a while, your program is thoroughly tested, and you still find no evidence for a bug. You begin to suspect that there might not be a bug after all. However, if there is no bug, you will have no purpose as a programmer. You feel as if your life depends on the existence of a bug. You are now looking for the Bug that will save you. You believe that there must be a Bug, so you test your program even more thoroughly. When you still cannot find any evidence for a Bug, you start to rationalize: Although I cannot find any Bug, that does not prove that there is no Bug. You are now a true believer in the Bug."


PS: A nice article, with pretty pictures.

2010-5-13: I am on Seth Robert's blog

2010-5-14: And then on boingboing


, (Seth Roberts, a professor emeritus of psychology from UC Berkeley) :
1. Absence of evidence is not evidence of absence. A _yhus explains why this is wrong. That such an Orwellian saying is popular in discussions of data suggests there are many ways we push away inconvenient data.
2. Correlation does not equal causation. In practice, this is used to mean that correlation is not evidence for causation. At UC Berkeley, a job candidate for a faculty position in psychology said this to me. I said, Isnt zero correlation evidence against causation? She looked puzzled.
3. The plural of anecdote is not data. How dare you try to learn from stories you are told or what you yourself observe!
Orwell was right. People use these sayings especially #1 and #3 to push away data that contradicts this or that approved view of the world. Without any data at all, the world would be simpler: We would simply believe what authorities tell us. Data complicates things. These sayings help those who say them ignore data, thus restoring comforting certainty.
Maybe there should be a term (antiscientific method ?) to describe the many ways people push away data. Or maybe preventive stupidity will do.
Absence of evidence is evidence of absence.
Very often stuff like this happens:
Somebody says "Kim, you are mistaken!", but no valid reasons are given.
Somebody says "God exists", but no valid reasons are given.
Somebody says "People are healed!", but there are no valid healings.

In all these cases, it is correct to become more certain that whatever
it is that is said, is wrong. The lack of evidence confirms that the saying is wrong.

Many people have an intuitive understanding that this is valid. Many
know that it is valid through experience. Many believe it is pure nonsense. A few know why it is valid.

I will below give an overview over a proof for the validity of arguments like this, with Bayesian statistics. (Jump over it if you want to).
Suppose that A <- B
The probability of event A is P(A)

One observes lack of B, that is !B

What is now the probability of A now that we know that B lacks? P( A | !B )

The usual is that P( A | !B ) = P( A & !B ) / ( P( A & !B ) + P( !A & !B ) )

Since A <- B, then P( !A & B ) = 0
which again means that P( !A & !B ) = P(!A) - P( !A & B ) = P(!A) - 0

This results in
P( A | !B ) = P( A & !B ) / ( P( A & !B ) + P(!A) )
( P( A & B ) + P( A & !B ) ) / ( P( A & B ) + P( A & !B ) + P(!A) ) = P(A)

( "

The conclusion is:

P( A | !B )
If one in addition assumes that P(B) > 0, then one gets

P( A | !B ) < P(A)

You, who jumped over the math can start reading again here.

Ergo, the conclusion is that every time one do not se it, then it is more likely to be untrue.

So every time somebody claims that people can levitate, but one do not see any levitating people, then one shall increase once confidence that people do not levitate.

And every time one do not see signs of small green men living in the radiator, then one shall be surer that they do not exist.

And every time one do not see valid evidence of Gods existence, one shall become surer that God do not exist.

, :Simply because this is the right way to think, just like 2+2=4 .. .

the reason for why people with claims should justify their clims themselves. Because if one claims something without evidence, that is evidence of being wrong. .

Kim0 2004-8-17