2) P(did not exercise | did not catch a cold) = 1/16
3) P(did not catch a cold | did not exercise) = 1/6
4) The events "did not exercise" and "did not catch a cold" are dependent events.
What is probability?
"Probability is a branch of mathematics which deals with finding out the likelihood of the occurrence of an event."
The formula of the probability of an event A is:
P(A) = n(A) / n(S)
where, n(A) is the number of favorable outcomes and n(S) is the total number of events in the sample space.
Conditional probability formula:
For events A, B,
P(A|B) means, event A and event B are depends on each other.
P(A | B) = n(A ∩ B) / P(B)
For given situation:
the total number of doctor’s patients: 8 + 30 + 10 + 2 =50
⇒ n(S) = 50
Let event A: did not exercise
⇒ n(A) = 10 + 2
⇒ n(A) = 12
⇒ P(A) = 12/50
event B: did not catch cold
⇒ n(B) = 30 + 2
⇒ n(B) =32
⇒ P(B) = 32/50
patient who did not catch a cold as well as who did not exercise = A ∩ B
⇒ n(A ∩ B) = 2
⇒ P(A ∩ B) = 2/50
2) To find: P(did not exercise | did not catch a cold)
⇒ P(A | B) = P(A ∩ B) / P(B)
⇒ P(A | B) = [tex]\frac{\frac{2}{50} }{ \frac{32}{50} }[/tex]
⇒ P(A | B) = 2/32
⇒ P(A | B) = 1/16
3) To find: P(did not catch a cold | did not exercise)
⇒ P(B | A) = P(B ∩ A) / P(A)
⇒ P(B | A) = [tex]\frac{ \frac{2}{50} }{ \frac{12}{50} }[/tex]
⇒ P(B | A) = 2/12
⇒ P(B | A) = 1/6
4) Since P(B | A) ≠ P(B)
i.e., P(did not catch a cold | did not exercise) ≠ P(did not catch a cold)
This means, the events "did not exercise" and "did not catch a cold" are dependent.
Learn more about probability here:
https://brainly.com/question/12478394
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