The probability of a toothache, given evidence of a cavity, P(toothache |…

2021

The probability of a toothache, given evidence of a cavity, P(toothache | cavity), is __________.

The full joint probability distribution for the Boolean variables Cavity, Toothache, and Catch is given below:

toothache ∧ catch

toothache ∧ ¬catch

¬toothache ∧ catch

¬toothache ∧ ¬catch

cavity

0.108

0.012

0.072

0.008

¬cavity

0.016

0.064

0.144

0.576

  1. A.

    0.400

  2. B.

    0.600

  3. C.

    0.280

  4. D.

    0.216

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Show answer & explanation

Correct answer: B

For events A and B with P(B) > 0, the conditional probability is defined as P(A | B) = P(A ∧ B) / P(B). When a full joint probability distribution is available, P(B) is found by summing every joint-probability cell in which B holds, and P(A ∧ B) is found by summing only the cells in which both A and B hold together.

Apply this to P(toothache | cavity) using the joint distribution above:

  1. Read off the cavity row of the table: the four joint probabilities are 0.108 (toothache, catch), 0.012 (toothache, ¬catch), 0.072 (¬toothache, catch), and 0.008 (¬toothache, ¬catch).

  2. Sum the whole row to get P(cavity): 0.108 + 0.012 + 0.072 + 0.008 = 0.200.

  3. Sum only the toothache-present cells within that row to get P(toothache ∧ cavity): 0.108 + 0.012 = 0.120.

  4. Divide: P(toothache | cavity) = P(toothache ∧ cavity) / P(cavity) = 0.120 / 0.200 = 0.600.

Cross-check: the remaining cavity-row cells give the complementary probability, (0.072 + 0.008) / 0.200 = 0.400. Since toothache and ¬toothache are the only two possibilities given cavity, the two conditional probabilities must add to 1 — and 0.600 + 0.400 = 1.000, confirming the answer.

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