Published by MBA Skool Team, Last Updated: April 15, 2016
What is Accept Errors?
Accept errors is terms during recruitment when a recruiter appoints an individual for a job profile for which who is not qualified, but is appointed for other reasons they feel would benefit the organization. The opposite of accept errors is reject errors.
In statistics, a type I error is the incorrect rejection of a null hypothesis which is true. A type II error is the failure to reject a null hypothesis which is false. Type I errors are known as false positive while type II errors are known as false negative.
A type I error leads a person to a conclusion that a fact exists when it does not.
A type II error leads a person to believe that a fact does not exists when it does exist.
In terms of false positive and false negative, a positive result is when a person rejects a null hypothesis while a negative result occurs when a person fails to reject a null hypothesis. So here positive= alternative and negative = null or the vice versa depending on the situation. So in these terms, a type I error is false positive (incorrectly choosing alternative hypothesis instead of null hypothesis) and a type II error is a false negative (incorrectly choosing the null hypothesis instead of the alternative hypothesis).
Null hypothesis (H0) is valid: Innocent
Null hypothesis (H0) is invalid: Guilty
Reject H0 I think he is guilty!
Type I error False positive Convicted!
Correct outcome True positive Convicted!
Don't reject H0 I think he is innocent!
Correct outcome True negative Freed!
Type II error False negative Freed!
Hence, this concludes the definition of Accept Errors along with its overview.
This article has been researched & authored by the Business Concepts Team. It has been reviewed & published by the MBA Skool Team. The content on MBA Skool has been created for educational & academic purpose only.
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