What Are the Tests for Independence in Probability Statistics?

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Homework Help Overview

The discussion revolves around the concepts of independence and mutual exclusivity in probability statistics, specifically examining events A and B with given probabilities. Participants are exploring how to determine the relationship between these events based on their probabilities.

Discussion Character

  • Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • Participants express confusion about how to determine if events are independent or mutually exclusive based solely on numerical probabilities. There are attempts to clarify definitions and relationships, particularly regarding the intersection of events.

Discussion Status

Some participants are actively seeking definitions and clarifications about the concepts of independence and mutual exclusivity. There is a recognition that if the intersection probability is zero, the events are mutually exclusive. However, uncertainty remains regarding the independence of the events, with references to external resources for further understanding.

Contextual Notes

Participants mention specific probabilities and seek to understand the implications of these values in the context of independence and mutual exclusivity. There is a noted reliance on definitions and external resources to guide the discussion.

Biochemgirl2002
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Homework Statement
2. Let A and B be events with P(A) = 0.5, P(B) = 0.3 and P(A
and B) = 0.8.
A. Find P(A∩B).
B. Are A and B independent events? Explain.
C. Are A and B mutually exclusive? Explain.
Relevant Equations
P(A or B) = P(A)-P(B)
A) (0.5)-(0.3)
=0.2

b)
c) i have no clue how to determine from just a set of numbers if they are independent or mutually exclusive
 
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rhiana said:
Homework Statement: 2. Let A and B be events with P(A) = 0.5, P(B) = 0.3 and P(A
and B) = 0.8.
A. Find P(A∩B).
B. Are A and B independent events? Explain.
C. Are A and B mutually exclusive? Explain.
Homework Equations: P(A or B) = P(A)-P(B)

A) (0.5)-(0.3)
=0.2

b)
c) i have no clue how to determine from just a set of numbers if they are independent or mutually exclusive
The first thing you need to do is look up some definitions.
What does ##P(A\cap B)## mean? (Hint: It does not mean ##P(A \text{ or } B)##.)
What does it mean for events to be independent?
What does it mean for events to be mutually exclusive?
 
tnich said:
The first thing you need to do is look up some definitions.
What does ##P(A\cap B)## mean? (Hint: It does not mean ##P(A \text{ or } B)##.)
What does it mean for events to be independent?
What does it mean for events to be mutually exclusive?
i think i believe that it means only the intercept between a and b
which i found out was actually zero

if there is no intercept then they are mutually exclusive,

now that i know this . i am still having trouble understanding if they are independent
i found this website (https://www.zweigmedia.com/RealWorl...t for Independence,if not, they are dependent.) where they say that if they don't follow those 3 equations they are independent, and so i believe it is independent
 
rhiana said:
i think i believe that it means only the intercept between a and b
which i found out was actually zero

if there is no intercept then they are mutually exclusive,

now that i know this . i am still having trouble understanding if they are independent
i found this website (https://www.zweigmedia.com/RealWorld/tutorialsf15e/frames7_5C.html#targetText=Test for Independence,if not, they are dependent.) where they say that if they don't follow those 3 equations they are independent, and so i believe it is independent
Right, ##P(A\cap B)## is the probability of the intersection of events (sets) ##A## and ##B##, and you are correct that if that probability is zero then the events are mutually exclusive.
The tests for independence that you found are correct, and the events are independent. The key concept here is that events are independent if knowing whether one occurred does not change the probability that the other occurred. That is the meaning of ##P(A|B)= P(A)##; the probability of ##A## given that you know ##B## has occurred is the the same as the probability of ##A## without knowledge of ##B##.
 

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