Probability independence problem

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  • #1
naptor
13
0

Homework Statement


Let
[itex]E= A \cup \bar{B} [/itex] and [itex]F= \bar{D} \cup C [/itex]
Assuming that A,B,C,D are independent show that
F and E are independent

Homework Equations


By definition A and by are independent if and only P(AB)=P(A)P(B).

The Attempt at a Solution


I tried to use set theory to simplify E[itex]\cap[/itex]F.But I couldn't imply the definition,all I got was this bunch of unions :
EF=[itex] A \bar{D} \cup A C \cup \bar{B} \bar{D} \cup \bar{B} C[/itex]
 
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  • #2
hi naptor! :smile:

start with, what is [itex]P(A \cup \bar{B})[/itex] ? :wink:
 
  • #3
tiny-tim said:
hi naptor! :smile:

start with, what is [itex]P(A \cup \bar{B})[/itex] ? :wink:

Hi tim :smile thanks for the reply

ok so :[itex]P(A \cup \bar{B})=P(A)+P(\bar{B})-P(A \cap \bar{B})[/itex] I can get rid off [itex]A \cap \bar{B}[/itex] using [itex]P(A)=P(A\cap B )+P(A \cap \bar{B}) \Rightarrow P(A \cap \bar{B}) =P(A)-P(A\cap B )[/itex] now I can plug this in my first eq and use the hypothesis I got:[itex]P(A \cup \bar{B})=P(A)+P(\bar{B})-P(A)P(\bar{B})[/itex] and the same thing for [itex]P(\bar{D}\cup C)[/itex]. I'm trying to combine these expressions in oder to get [itex]P(E \cap F)=P(E)P(F)[/itex].
Am I on the right track?
 
Last edited:
  • #4
hi naptor! :smile:
naptor said:
[itex]P(A \cup \bar{B})=P(A)+P(\bar{B})-P(A \cap \bar{B})[/itex] I can get rid off [itex]A \cap \bar{B}[/itex] using [itex]P(A)=P(A\cap B )+P(A \cap \bar{B}) \Rightarrow P(A \cap \bar{B}) =P(A)-P(A\cap B )[/itex] now I can plug this in my first eq and use the hypothesis I got:[itex]P(A \cup \bar{B})=P(A)+P(\bar{B})-P(A)P(\bar{B})[/itex]

a bit long-winded, and you still have a P(A), which should have canceled :redface:

easier would have been [itex]P(A \cup \bar{B})=P(\bar{B})+P(A \cap B)[/itex] :wink:

try again :smile:
 
  • #5
naptor said:

Homework Statement


Let
[itex]E= A \cup \bar{B} [/itex] and [itex]F= \bar{D} \cup C [/itex]
Assuming that A,B,C,D are independent show that
F and E are independent

Homework Equations


By definition A and by are independent if and only P(AB)=P(A)P(B).

The Attempt at a Solution


I tried to use set theory to simplify E[itex]\cap[/itex]F.But I couldn't imply the definition,all I got was this bunch of unions :
EF=[itex] A \bar{D} \cup A C \cup \bar{B} \bar{D} \cup \bar{B} C[/itex]

It is a lot easier to first recognize some easily-proven preliminary properties: (i) two events [itex] U \text{ and } V[/itex] are independent if and only if [itex] U \text{ and } \bar{V}[/itex] are independent; and (ii) If [itex]U, V, W [/itex] are independent, then [itex] U \text{ and } V \cup W [/itex] are independent, as are [itex] U \text{ and } V \cap W [/itex].

Because of these properties it does not matter whether we use [itex] B \text{ or } \bar{B}[/itex] and it does not matter whether we use [itex] C \text{ or } \bar{C}. [/itex] So, we can ask instead whether [itex] A \cup B \text{ and } \bar{C} \cup \bar{D} [/itex] are independent, or equivalently, whether [itex]A \cup B \text{ and } C \cap D [/itex] are independent. This last form is easier to work with. We have
[tex] P\{ (A \cup B)\cap( C \cap D) \} = P\{ (A \cap C \cap D) \cup (B \cap C \cap \D) \}\\
= P\{A \cap (C \cap D) \} + P\{B \cap (C \cap D) \} – P\{ (A \cap B)\cap(C \cap D)\} \\
= P\{A\} P\{C \cap D\} + P\{B\} P\{C \cap D\} – P\{A \cap B \}P\{ C \cap D\}\\
= P\{ A \cup B\} P\{ C \cap D\},[/tex]
so [itex] A \cup B \text{ and } C \cap D[/itex] are independent.

RGV
 

FAQ: Probability independence problem

1. What is the probability independence problem?

The probability independence problem is a concept in statistics and probability theory that deals with the relationship between two events. It refers to the question of whether the occurrence of one event has any influence on the probability of the other event occurring. In other words, if two events are independent, the probability of one event occurring is not affected by the occurrence of the other event.

2. How do you determine if two events are independent?

To determine if two events are independent, you can use the multiplication rule of probability. If the probability of both events occurring together is equal to the product of their individual probabilities, then the events are considered independent. You can also use statistical methods such as correlation analysis to determine the relationship between the two events.

3. What are the implications of events being independent?

If two events are independent, it means that the occurrence of one event does not affect the probability of the other event occurring. This has important implications in various fields such as economics, finance, and science. For example, in a coin toss, the outcome of one toss does not affect the outcome of the next toss, making the events independent.

4. What is the difference between independent and mutually exclusive events?

Independent events are events where the occurrence of one event does not affect the probability of the other event occurring. On the other hand, mutually exclusive events are events that cannot occur at the same time. In other words, if one event occurs, the other event cannot occur. For example, in a dice roll, getting an even number and getting a 3 are mutually exclusive events, but getting an even number and getting a 4 are independent events.

5. How does the concept of independence apply to real-world situations?

The concept of independence is applicable in various real-world situations, such as in medical research and insurance. In medical research, independence is important to ensure that the results of a study are not influenced by external factors. In insurance, independence is used to calculate insurance premiums, where the probability of one event (such as a car accident) occurring should not affect the probability of another event (such as a house fire) occurring.

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