Type I and Type II Errors

URL

http://intuitor.com/statistics/T1T2Errors.html

Description

Type I and Type II Errors explained: It only takes one good piece of evidence to send a hypothesis down in flames but an endless amount to prove it correct. If the null is rejected then logically the alternative hypothesis is accepted. This is why both the justice system and statistics concentrate on disproving or rejecting the null hypothesis rather than proving the alternative. It's much easier to do. If a jury rejects the presumption of innocence, the defendant is pronounced guilty.

Type I errors: Unfortunately, neither the legal system or statistical testing are perfect. A jury sometimes makes an error and an innocent person goes to jail. Statisticians, being highly imaginative, call this a type I error. Civilians call it a travesty.

In the justice system, failure to reject the presumption of innocence gives the defendant a not guilty verdict. This means only that the standard for rejecting innocence was not met. It does not mean the person really is innocent. It would take an endless amount of evidence to actually prove the null hypothesis of innocence.

Type II errors: Sometimes, guilty people are set free. Statisticians have given this error the highly imaginative name, type II error.