Mutually exclusive and exclusive

  • Thread starter denian
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In summary, probability deals with the likelihood of events occurring. Mutually exclusive events are those that cannot happen at the same time, while independent events are those that do not affect each other's probability of occurring.
  • #1
denian
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currently, I am studying probability in my school.

i'm bit confused with the difference btw :-
(a) mutually exclusive and exclusive
(b) independent and mutually exclusive.

anyone can explain?
 
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  • #2
(a) I'm not sure what you are trying to describe.
(b) Mutually exclusive - the probability that both will happen is 0.
Independent - probability that both will happen is the product of the probabilities of the individual events.
 
  • #3
I'm with mathedman. I have never heard the term "exclusive" used in probability except as part of "mutually exclusive". I would be inclined to say that "exclusive" and "mutually exclusive" are the same thing.

As mathedman said: if two events are "mutually exclusive" then the probability of both happening is 0 (P(A and B)= 0). If they are independent, P(A and B)= P(A)*P(B).
 
  • #4
Or, in linguistic terms:

If two events are mutually exclusive, then it is impossible for both to happen-- the occurence of one necessarily excludes any chance that the other occurs.

If two events are independent, then they do not influence each other-- the occurence of one does not change the probability that the other will happen.

For instance, let
A: the event that I leave my house to go to my 9-5 job today
B: the event that I sleep in my house until 5pm today
C: the event that someone calls my home phone number
D: the event that a coin flip comes up heads

A and B are mutually exclusive events, since if I sleep until 5pm I can't go to work that day, and likewise if I go to work then I must have been awake before 5pm. A and C are not mutually exclusive, since going to work does not exclude the possibility that someone places a call to my home phone, and vice versa.

A and D are independent events, since my going to work does not affect the chance that a coin flip comes up heads, and vice versa (assuming I'm not fatalistic enough to base my decisions on a coin toss, of course). However, B and C are not independent events, since if I sleep until 5pm, my sleepiness affects a greater chance that someone (my overly demanding employer, for one ) will call my house to see what's going on.

Actually, it is useful to think of mutual exclusion and independence as exact opposite relations. If two events X and Y are independent, then knowing that X occurs gives you absolutely no relevant information as to the probability of Y occurring. On the other hand, if X and Y are mutually exclusive, then knowing that X occurs gives you complete information as to the probability of Y occurring, since you know that there is no chance that Y can occur.
 
Last edited:

1. What is the difference between mutually exclusive and exclusive?

Mutually exclusive means that two events cannot occur at the same time, while exclusive means that something is restricted to a particular group or category.

2. Can two events be both mutually exclusive and exclusive?

No, if two events are mutually exclusive, it means that they cannot occur at the same time, making them automatically exclusive as well.

3. How can I identify if two events are mutually exclusive?

Two events are considered mutually exclusive if they cannot occur at the same time. This means that the probability of both events happening together is zero.

4. Are mutually exclusive and exclusive interchangeable terms?

No, although they may seem similar, mutually exclusive and exclusive have different meanings in statistics. Mutually exclusive refers to two events, while exclusive can refer to a broader category or group.

5. What is the purpose of understanding mutually exclusive and exclusive events in science?

Understanding mutually exclusive and exclusive events is important in science because it helps us to accurately calculate probabilities and make informed decisions based on data analysis. It also allows us to properly design experiments and control variables.

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