Answer:
0.1998
Step-by-step explanation:
This is a conditional probability question.
We solve this question using Bayes's Theorem of conditional probability.
P(A|B) = [P(B|A) × P(A)] ÷ [(P(B|A) × P(A))+ (P(B|A') × P(A'))]
Based on the information in the question, we have the following values.
Suppose it snows in Greenland once every 27 days.
Probability (it snows) = P(A) = 1/27
= 0.037037037
Approximately = 0.0370
Probability ( it doesn't snow) = P(A') = 1 - 0.0370 = 0.963
Probability ( that when it snow, glaciers grow) = P(B|A) = 26% = 0.26
Probability( that is doesn't snow , glaciers grow) = P(B|A)' = 4% = 0.04
Using the Bayes's Theorem of conditional probability
Probability that it is snowing in Greenland when glaciers are growing is =
P(A|B) = [P(B|A) × P(A)] ÷ [(P(B|A) × P(A))+ (P(B|A') × P(A'))]
= [0.26 × 0.0370] ÷ [(0.26 × 0.0370) + (0.04 × 0.963)]
= 0.00962 ÷( 0.00962 + 0.03852)
=0.00962 ÷ 0.04814
= 0.199833818
Approximately to 4 decimal places ≈ 0.1998
Therefore, probability that it is snowing in Greenland when glaciers are growing is 0.1998
