In September, 60% days are rainy & 40% are sunny.Metrology department wrongly predicts 10% of the times in rainy days and 20% on sunny days.Weather forecast indicates a day to be sunny.What is the probability that the forecast will be proved wrong?
Let "R" be the event that a day is rainy, "S" be the event that a day is sunny
Let "W" be the event that the forecast will be wrong
Then by using Bayes’ theorem
"=\\dfrac{0.2(0.4)}{0.1(0.6)+0.2(0.4)}=\\dfrac{4}{7}\\approx0.5714"
The probability that the forecast will be proved wrong is "\\dfrac{4}{7}\\approx0.5714".
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