Bayes Theorem کا حساب کیسے لگائیں
Bayes Theorem کیا ہے؟
Applies Bayes theorem updating probability based on new evidence. Foundation of probabilistic reasoning.
فارمولا
P(A|B) = P(B|A) × P(A) ÷ P(B)
- P
- overall probability of evidence — overall probability of evidence
- A
- likelihood of evidence given A — likelihood of evidence given A
- B
- overall probability of evidence — overall probability of evidence
مرحلہ وار گائیڈ
- 1P(A|B) = P(B|A) × P(A) ÷ P(B)
- 2P(A|B) = posterior (updated probability)
- 3P(A) = prior probability
- 4P(B|A) = likelihood of evidence given A
- 5P(B) = overall probability of evidence
حل شدہ مثالیں
ان پٹ
P(A), P(B|A), P(B)
نتیجہ
P(A|B) calculated
عام غلطیاں جن سے بچنا ہے
- ✕Confusing conditional probabilities
- ✕Not updating priors properly
- ✕Forgetting normalization constant P(B)
اکثر پوچھے جانے والے سوالات
What's practical example?
Medical test: prior disease probability, test accuracy, posterior if positive test result.
Why is Bayes important?
Foundation of statistical inference, machine learning, and decision-making under uncertainty.
حساب کے لیے تیار ہیں؟ مفت Bayes Theorem کیلکولیٹر آزمائیں۔
اسے خود آزمائیں →