# Type 1 Error Example

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A type I error means that not only has an innocent person been sent to jail but the truly guilty person has gone free. 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. Statisticians have given this error the highly imaginative name, type II error. This means only that the standard for rejectinginnocence was not met. have a peek here

Here the null hypothesis indicates that the product satisfies the customer's specifications. Both statistical analysis and the justice system operate on samples of data or in other words partial information because, let's face it, getting the whole truth and nothing but the truth The null hypothesis has to be rejected beyond a reasonable doubt. In the justice system, failure to reject the presumption of innocence gives the defendant a not guilty verdict. http://support.minitab.com/en-us/minitab/17/topic-library/basic-statistics-and-graphs/hypothesis-tests/basics/type-i-and-type-ii-error/

## Probability Of Type 1 Error

Straight Dope Message Board > Main > General Questions Type I vs Type II error: can someone dumb this down Others are similar in nature such as the British system which inspired the American system) True, the trial process does not use numerical values while hypothesis testing in statistics does, but In both the judicial system and statistics the null hypothesis indicates that the suspect or treatment didn't do anything. It does not mean the person really is innocent.

Justice System - Trial Defendant Innocent Defendant Guilty Reject Presumption of Innocence (Guilty Verdict) Type I Error Correct Fail to Reject Presumption of Innocence (Not Guilty Verdict) Correct Type II Civilians call it a travesty. In other words, nothing out of the ordinary happened The null is the logical opposite of the alternative. Type 3 Error If the null hypothesis is rejected for a batch of product, it cannot be sold to the customer.

A jury sometimes makes an error and an innocent person goes to jail. Probability Of Type 2 Error These questions can be understood by examining the similarity of the American justice system to hypothesis testing in statistics and the two types of errors it can produce.(This discussion assumes that Americans find type II errors disturbing but not as horrifying as type I errors. https://en.wikipedia.org/wiki/Type_I_and_type_II_errors A data sample - This is the information evaluated in order to reach a conclusion.

In statistical hypothesis testing used for quality control in manufacturing, the type II error is considered worse than a type I. Types Of Errors In Accounting Also please note that the American justice system is used for convenience. If the null is rejected then logically the alternative hypothesis is accepted. The null hypothesis - In the criminal justice system this is the presumption of innocence.

## Probability Of Type 2 Error

This emphasis on avoiding type I errors, however, is not true in all cases where statistical hypothesis testing is done. Rejecting a good batch by mistake--a type I error--is a very expensive error but not as expensive as failing to reject a bad batch of product--a type II error--and shipping it Probability Of Type 1 Error Colors such as red, blue and green as well as black all qualify as "not white". Type 1 Error Psychology As mentioned earlier, the data is usually in numerical form for statistical analysis while it may be in a wide diversity of forms--eye-witness, fiber analysis, fingerprints, DNA analysis, etc.--for the justice

This can result in losing the customer and tarnishing the company's reputation. navigate here A standard of judgment - In the justice system and statistics there is no possibility of absolute proof and so a standard has to be set for rejecting the null hypothesis. It only takes one good piece of evidence to send a hypothesis down in flames but an endless amount to prove it correct. In the justice system the standard is "a reasonable doubt". Type 1 Error Calculator

In statistics the standard is the maximum acceptable probability that the effect is due to random variability in the data rather than the potential cause being investigated. In a sense, a type I error in a trial is twice as bad as a type II error. In statistics the alternative hypothesis is the hypothesis the researchers wish to evaluate. Check This Out Statisticians, being highly imaginative, call this a type I error.

Password Type I errors: Unfortunately, neither the legal system or statistical testing are perfect.

For example "not white" is the logical opposite of white. This standard is often set at 5% which is called the alpha level. Type II errors: Sometimes, guilty people are set free. Power Of The Test Needless to say, the American justice system puts a lot of emphasis on avoiding type I errors.

It would take an endless amount of evidence to actually prove the null hypothesis of innocence. If a jury rejects the presumption of innocence, the defendant is pronounced guilty.