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Conditional probability for medical testing in a forest

Here, we denote by \sim A the event NOT A.

Example 1: Squirrel Flu Testing

In a forest, a group of squirrels is concerned about a new illness called “Squirrel Flu.” It’s more dangerous than the ordinary flu. From the data collected, they know that

  • Probability of a squirrel having Squirrel Flu P(SF)= 0.1
  • Probability of testing positive if a squirrel has Squirrel Flu P(T|SF)=0.9
  • Probability of testing positive if a squirrel does not have Squirrel Flu P(T|\sim SF)= 0.2

Now, A squirrel named Nutty takes the test and it comes back positive. What is the probability that Nutty actually has Squirrel Flu?

Answer:

Using Bayes’ Theorem:

P(SF|T) = \frac{P(T|SF) \cdot P(SF)}{P(T|SF) \cdot P(SF) + P(T|\sim SF) \cdot P(\sim SF)}

Now:

  • P(T|SF) = 0.9
  • P(SF) = 0.1
  • P(T|\sim SF) = 0.2
  • P(\sim SF) = 1 - P(SF) = 0.9

Hence,

P(SF|T) = \frac{0.9 \cdot 0.1}{0.9 \cdot 0.1 + 0.2 \cdot 0.9} = \frac{0.09}{0.09 + 0.18} = \frac{0.09}{0.27} = \frac{1}{3} \approx 0.333

So, Nutty has about a 33.3% chance of actually having Squirrel Flu upon testing positive.

Example 2: Deer Allergy Testing

In the forest, some deer have allergies to a particular type of flower.

  • Probability of a deer having allergies P(A)= 0.15
  • Probability of the test detecting allergies if the deer has them P(T|A)= 0.85
  • Probability of the test being positive if the deer does not have allergies P(T|\sim A)=0.05

Now, a deer named Nambi tests positive for allergies. What is the probability that Nambi actually has allergies?

Using Bayes’ Theorem:

P(A|T) = \frac{P(T|A) \cdot P(A)}{P(T|A) \cdot P(A) + P(T|\sim A) \cdot P(\sim A)}

Now:

  • P(T|A) = 0.85
  • P(A) = 0.15
  • P(T|\sim A) = 0.05
  • P(\sim A) = 1 - P(A) = 0.85

So,

P(A|T) = \frac{0.85 \cdot 0.15}{0.85 \cdot 0.15 + 0.05 \cdot 0.85} = \frac{0.1275}{0.1275 + 0.0425} = \frac{0.1275}{0.17} \approx 0.75

So, Nambi has about a 75% chance of actually having allergies upon testing positive.

These examples show how conditional probability can help forest creatures interpret their medical test results.

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