## Snapdeal Interview Question | Concepts

Question

Can you explain the concept of a false positive and false negative? Give some examples to make things clear.

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1. False Positive is the Type-I Error
False Negative is the Type-II Error. These two errors occur during Hypothesis Test.
Example:
We all know that the decision made by the court is not always correct. If a person is declared guilty at the end of the trial then there are two possibilities:
1. The person has not committed a crime and is declared guilty.
2. The person has committed a crime and is rightfully declared guilty.
In the first case, the court has made an error by punishing an innocent person. In statistics, this kind of error is called Type I Error or False Positive or alpha error.
Formal Definition of Type-I Error is: A type-I Error occurs when a true null hypothesis is rejected.
Now suppose that in the court trial case the person is declared not guilty at the end of the trial. Such a verdict does not indicate that the person has indeed not committed the crime. It is possible that the person is guilty but there is not enough evidence to prove the guilt. Consequently, in this situation, there are again two possibilities.
1. The person has not committed the crime and is declared not guilty.
2. The person has committed the crime but, because of the lack of enough evidence, is declared
not guilty. In the first case, the courtâ€™s decision is correct. In the second case, however, the court has
committed an error by setting a guilty person free. In statistics, this type of error is called a Type II or Beta error.
Formal Definition of Type-II Error: A Type II error occurs when a false null hypothesis is not rejected.
The value of 1- Beta is called the power of the test. It represents the probability of not making a Type II error.