Probability question: Independant events

I have been reading this book:

On page 48, the book says:
“Let Ω = [0,1], A = [0,1/4] as before; then A is independant of B = [1/8,5/8] and of C = [1/8,3/8] U [3/4,1]. In addidtion, B and C are independant. However, P(A∩B∩C) ≠ P(A)P(B)P(C). Thus, given three events, the pairwise independance of each of the three possible pairs does not sufice for the extension of ‘independance’ to all three events.”

When I first read this I was like :dubious: so I put together a spreadsheet using the RAND function to get over 100000 rows of random numbers in columns A,B and C. In column D I put a big IF statment that returns a 1 if event A above occurs in column A and event B occurs in column B etc. It returns 0 if even one of the events do not occur.

On their own, I calculate the probability of event A = 0.25, P(B) = 0.5, P(C) = 0.5
Then P(A)P(B)P(C) = 0.0625

If I do a sum of column D on my spreadsheet and divide that by a count then it gets quite close to 0.0625. Obviously never exacly the same but never too far.

So what is the author on about?

Independent events should always be multiplied together, and .0625 is what you get from (0.5)(0.5)(0.25).

The problem is that A∩B∩C = A∩B = A∩C – it’s the interval [1/8,1/4], and so has probability 0.125. You don’t need a spreadsheet with random functions for that: you just need to draw a diagram, and see on that where sets A, B and C intersect.

So are you saying, based on what I have quoted above, that the book is no good?

I don’t think that approach is appropriate for independant events.

What you are saying is as if I only had random numbers in one column and was testing for each condition (A,B,C) on this column.
As these are all independant, each condition is tested on a sepparate column of random numbers. So the result is different. No?

If you are taking random numbers in the interval [0,1], then:

A is satisfied if the number is between 0 and 1/4
B is satisfied if the number is between 1/8 and 5/8
C is satisfied if the number is between 1/8 and 3/8, or between 3/4 and 1

So all three of A, B and C are satisfied if the number is between 1/8 and 1/4 – but each time you should be checking the same number.

Is that how your spreadsheet works?

It is more like this:

A is satisfied if the number1 is between 0 and 1/4
B is satisfied if the number2 is between 1/8 and 5/8
C is satisfied if the number3 is between 1/8 and 3/8, or between 3/4 and 1

Also, I have just realised the point the author was making:
The probability of the intersection does not = the product of the probabilities for independant events. So you calculaiton of 0.125 does not = 0.0625

I still think your missing the main point which is that even though any pair of these events is independent, the combination of all three isn’t.

From the example
P(A)=1/4 (area between 0 and 1/4)
P(B)=1/2 (area between 1/8 and 5/8)
P©=1/2 (area between 1/8 and 3/8, or between 3/4 and 1)

The probability of the intersection
P(A and B) = 1/8 (area between 1/8 and 1/4) = P(A)*P(B) so (A and B are independent)
P(A and C) = 1/8 (area between 1/8 and 1/4) = P(A)*P© so (A and C are independent)
P(B and C) = 1/4 (area between 1/8 and 3/8) = P(B)*P© so (B and C are independent)

However P(A and B and C) = 1/8 (area between 1/8 and 1/4)
While P(A)*P(B)*P© = 1/16 so the triplet (A,B,C) is not independent.

By themselves knowing I’m in region A tells me nothing about whether I’m in region B (I have a 1/4 chance whether B is true or not) and vis-versa P(B)=P(B|A)=P(B|!A)=1/2

Similarly A and C provide no information about each other, and B and C provide no information about each other.

However in combination, if I know that B and C are both true, then that tells me that A must be true. So even though every pair is independent, the whole set of events isn’t.

Here is simpler example: I flip 2 coins and define the following three events.

A = first coin is heads
B = second coin is heads
C = both coins show the same face.

It is clear that A and B are independent, since there is no relationship. Also I just know A that the first coin is a head, I still don’t have any information about whether the 2 coins have the same face, so A and C are independent. Similarly B and C are independent. However knowledge of both A and B in combination gives me complete knowledge of C. So the combined three events aren’t independent.

Another example:

Roll a four-sided die. Let A = {1, 2}, B = {2, 4} and C = {2, 3}.

P(A and B) = 1/4 = P(A)P(B)
P(A and C) = 1/4 = P(A)P©
P(B and C) = 1/4 = P(B)P©

However, P(A and B and C) = 1/4, but P(A)P(B)P© = 1/8. So the events A, B and C are pairwise independent, but not independent.

You were right, I was missing that point :smack:

Thanks to Buck Godot and ultrafilter for clearing that up.