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#6: Post edited by user avatar DNB‭ · 2021-08-20T23:10:11Z (over 2 years ago)
  • Besides guaranteeing $0 \le P(A ∩ B) \le 1$, why can't Independence be defined as P(A ∩ B) = P(A) +,-, or ÷ P(B)?
  • Besides guaranteeing 0 ≤ P(A ∩ B) ≤ 1, why can't Independence be defined as P(A ∩ B) = P(A) +,-, or ÷ P(B)?
#5: Post edited by user avatar DNB‭ · 2021-08-20T08:13:19Z (over 2 years ago)
  • Besides guaranteeing that $0 \le P(A ∩ B) \le 1$, why can't Independence be defined as P(A ∩ B) = P(A) +,-, or ÷ P(B)?
  • Besides guaranteeing $0 \le P(A ∩ B) \le 1$, why can't Independence be defined as P(A ∩ B) = P(A) +,-, or ÷ P(B)?
#4: Post edited by user avatar DNB‭ · 2021-08-20T08:13:05Z (over 2 years ago)
  • Why isn't Independence defined as $P(A \cap B) = P(A) +,-,\text{or} ÷ P (B)$?
  • Besides guaranteeing that $0 \le P(A ∩ B) \le 1$, why can't Independence be defined as P(A B) = P(A) +,-, or ÷ P(B)?
  • In the title, ? = one of the four elementary arithmetic operations. Why isn't independence defined as $P(A \cap B) = P(A)$
  • 1. $+ P (B)$?
  • 2. or $- P (B)$?
  • 3. or $÷ P (B)$?
  • >### Definition 2.5.1 (Independence of two events).
  • >Events A and B are _independent_ if
  • $P(A \cap B) = P(A)P(B)$.
  • >If P(A) > 0 and P(B) > 0, then this is equivalent to
  • $P(A|B) = P(A)$;
  • and also equivalent to $P(B|A) = P(B)$.
  • Blitzstein, *Introduction to Probability* (2019 2 ed), p 63.
  • >We have introduced the conditional probability P(A|B) to capture the partial
  • information that event B provides about event A. An interesting and important
  • special case arises when the occurrence of B provides no such information and
  • does not alter the probability that A has occurred, i.e. ,
  • P(A I B) = P(A).
  • When the above equality holds. we say that A is **independent** of B. Note that
  • by the definition $P(A | B) = P(A \cap B)/P(B)$, this is equivalent to
  • $P(A \cap B) = P(A)P (B).$
  • We adopt this latter relation as the definition of independence because it can be
  • used even when P(B) = 0, in which case P(A|B) is undefined. The symmetry
  • of this relation also implies that independence is a symmetric property; that is,
  • if A is independent of B, then B is independent of A, and we can unambiguously
  • say that A and B are **independent events**.
  • Tsitsiklis, *Introduction to Probability* (2008 2e), p 34.
  • I know that $0 \le P(A \cap B) \le 1$ will be violated if $P(A \cap B) = P(A) +,-,\text{or} ÷ P (B)$. I'm not asking about or challenging this reason.
  • But what are the other reasons against defining independence as $P(A \cap B) = P(A)$
  • 1. $+ P (B)$?
  • 2. or $- P (B)$?
  • 3. or $÷ P (B)$?
  • >### Definition 2.5.1 (Independence of two events).
  • >
  • >Events A and B are _independent_ if
  • $P(A \cap B) = P(A)P(B)$.
  • >
  • >If P(A) > 0 and P(B) > 0, then this is equivalent to
  • $P(A|B) = P(A)$;
  • and also equivalent to $P(B|A) = P(B)$.
  • Blitzstein, *Introduction to Probability* (2019 2 ed), p 63.
  • >We have introduced the conditional probability P(A|B) to capture the partial
  • information that event B provides about event A. An interesting and important
  • special case arises when the occurrence of B provides no such information and
  • does not alter the probability that A has occurred, i.e. ,
  • P(A I B) = P(A).
  • When the above equality holds. we say that A is **independent** of B. Note that
  • by the definition $P(A | B) = P(A \cap B)/P(B)$, this is equivalent to
  • $P(A \cap B) = P(A)P (B).$
  • We adopt this latter relation as the definition of independence because it can be
  • used even when P(B) = 0, in which case P(A|B) is undefined. The symmetry
  • of this relation also implies that independence is a symmetric property; that is,
  • if A is independent of B, then B is independent of A, and we can unambiguously
  • say that A and B are **independent events**.
  • Tsitsiklis, *Introduction to Probability* (2008 2e), p 34.
#3: Post edited by user avatar DNB‭ · 2021-07-29T08:03:52Z (over 2 years ago)
  • Why isn't independence defined as $P(A \cap B) = P(A) +,-,\text{or} ÷ P (B)$?
  • Why isn't Independence defined as $P(A \cap B) = P(A) +,-,\text{or} ÷ P (B)$?
#2: Post edited by user avatar DNB‭ · 2021-07-29T08:02:33Z (over 2 years ago)
  • Why isn't independence defined as $P(A \cap B) = P(A) ? P (B)$?
  • Why isn't independence defined as $P(A \cap B) = P(A) +,-,\text{or} ÷ P (B)$?
#1: Initial revision by user avatar DNB‭ · 2021-07-29T08:02:00Z (over 2 years ago)
Why isn't independence defined as $P(A \cap B) = P(A) ? P (B)$? 
In the title, ? = one of the four elementary arithmetic operations. Why isn't independence defined as $P(A \cap B) = P(A)$

1. $+ P (B)$?

2. or $- P (B)$?

3. or $÷ P (B)$?

>### Definition 2.5.1 (Independence of two events). 

>Events A and B are _independent_ if
$P(A \cap B) = P(A)P(B)$.

>If P(A) > 0 and P(B) > 0, then this is equivalent to
$P(A|B) = P(A)$;
and also equivalent to $P(B|A) = P(B)$.

Blitzstein, *Introduction to Probability* (2019 2 ed), p 63. 

>We have introduced the conditional probability P(A|B) to capture the partial
information that event B provides about event A. An interesting and important
special case arises when the occurrence of B provides no such information and
does not alter the probability that A has occurred, i.e. ,
P(A I B) = P(A).
When the above equality holds. we say that A is **independent** of B. Note that
by the definition $P(A | B) = P(A \cap B)/P(B)$, this is equivalent to
$P(A \cap B) = P(A)P (B).$
We adopt this latter relation as the definition of independence because it can be
used even when P(B) = 0, in which case P(A|B) is undefined. The symmetry
of this relation also implies that independence is a symmetric property; that is,
if A is independent of B, then B is independent of A, and we can unambiguously
say that A and B are **independent events**.

Tsitsiklis, *Introduction to Probability* (2008 2e), p 34.