Probability - proving independence/dependence

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D1 and D2 are dependent.In summary, the conversation discusses the independence of two events, "to have defect D1" and "to have defect D2," in a film production process. While the initial calculations suggest that they are independent, further analysis using the definition of independence and the Addition Rule of probability shows that they are actually dependent.
  • #1
jasper10
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Homework Statement



A film is defective either when the level of sensitivity is wrong (defect D1) or when the colours are faulty (defect D2). 2% of all films made have at least one of these two defects. 1% of all films have defect D1 and 0.2% of all films have both defect D1 and D2.

Are the events "to have defect D1" and "to have defect D2" independent?

The Attempt at a Solution



P(D1) = 0.01
P(D1 ∩ D2) = 0.002
P(D1 ∪ D2) = 0.02

If independent, then: P(D1 ∪ D2) = P(D1) + P(D2) = 0.02

hence P(D2) = 0.02 - P(D1) = 0.02 - 0.01 = 0.01

P(D1 ∩ D2) = 0.01 x 0.01 = 0.0001 which is not 0.002

Is this correct? How do I prove that they are DEPENDENT, as all i have done is rejected their independency!

Thank you very much!
 
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  • #2
Go back to your textbook and read the definitions of "dependent" and "independent" events!
 
  • #3
They're independent. It's just a tree with two branches for D1 and two branches each for D2.
 
  • #4
Again, look at the definition of independence - and, since you used it, look at the correct form for the Addition Rule of probability.
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"They're independent. It's just a tree with two branches for D1 and two branches each for D2."
**************************
Makes no sense here.
 
  • #5
statdad said:
Again, look at the definition of independence - and, since you used it, look at the correct form for the Addition Rule of probability.
**************************
"They're independent. It's just a tree with two branches for D1 and two branches each for D2."
**************************
Makes no sense here.

Why not?

[PLAIN]http://dl.dropbox.com/u/704818/Tree.png
 
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  • #6
Pr(D1 ∪ D2) = P(D1) + P(D2) - P(D1 ∩ D2)
0.02 = 0.01 + P(D2) - 0.0002
P(D2) = 0.0102

P(D1 ∩ D2) = 0.0002 != 0.01 * 0.0102 -> D1 and D2 are dependent.

PD1(D2) = P(D2)/P(D1) = P(D1 ∩ D2)/P(D1) = 0.0002/0.01 = 0.02
 

FAQ: Probability - proving independence/dependence

What is probability?

Probability is a measure of how likely an event is to occur. It is expressed as a number between 0 and 1, with 0 representing impossibility and 1 representing certainty.

What is independence in probability?

In probability, independence refers to the lack of a relationship between two events. This means that the occurrence of one event does not affect the probability of the other event happening.

How do you prove independence in probability?

To prove independence in probability, you must show that the probability of one event occurring is not affected by the occurrence of another event. This can be done through mathematical calculations or by demonstrating that the events are not related in any way.

What is dependence in probability?

Dependence in probability refers to the relationship between two events where the occurrence of one event affects the probability of the other event happening. This can be positive dependence, where the occurrence of one event increases the probability of the other event happening, or negative dependence, where the occurrence of one event decreases the probability of the other event happening.

How do you prove dependence in probability?

To prove dependence in probability, you must show that the occurrence of one event has an impact on the probability of the other event happening. This can be done through mathematical calculations or by demonstrating a clear relationship between the events.

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