False positives and false negatives: disease screening - conditional probability - Bayes Theorem

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This video explains about risk and screening, and shows how to calculate and express rates of false positives and false negatives. An imaginary disease, "Earpox" is used for the examples.
Risk is another name for probability.
0:45 Earpox represents cancer, infectious diseases, mental illness, lie detection, recruitment decisions.
1:00 Prevalence
1:25 Sensitivity
1:45 Specificity
2:34 Icon diagram
5:00 conditional probability table
6:50 using the table to answer questions.

This extremely important video for anyone getting screening done for themselves or others. We generally underestimate how likely it is that a positive result is a false positive.
#DrNicStats #Probability

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One of the best explanations - thank you.

davidjoelsen

hey I was very confused with this topic but really thanks to you I've received one of the best explaination and i solved that problem you gave and answer is
total negative results probability is 0.90 or 9/10
and the chances where the test says the patient is negative but they have disease are 0.03 or 1/300
please reply am i correct or not
thankyou,

sahilvichare

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