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## Probability Of Type 1 Error

## Probability Of Type 2 Error

## In other words, nothing out of the ordinary happened The null is the logical opposite of the alternative.

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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 Password

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 Needless to say, the American justice system puts a lot of emphasis on avoiding type I errors. It does not mean the person really is innocent. Statisticians, being highly imaginative, call this a type I error.

If the null hypothesis is rejected for a batch of product, it cannot be sold to the customer. For example "not white" is the logical opposite of white. Type I errors: Unfortunately, neither the legal system or statistical testing are perfect. It only takes one good piece of evidence to send a hypothesis down in flames but an endless amount to prove it correct.

In both the judicial **system and statistics the null** hypothesis indicates that the suspect or treatment didn't do anything. The null hypothesis has to be rejected beyond a reasonable doubt. This can result in losing the customer and tarnishing the company's reputation. Type 3 Error In a sense, a type I error in a trial is twice as bad as a type II error.

If a jury rejects the presumption of innocence, the defendant is pronounced guilty. Probability Of Type 2 Error In the justice system the standard is "a reasonable doubt". 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 https://en.wikipedia.org/wiki/Type_I_and_type_II_errors 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

It would take an endless amount of evidence to actually prove the null hypothesis of innocence. Types Of Errors In Accounting This emphasis on avoiding type I errors, however, is not true in all cases where statistical hypothesis testing is done. Straight Dope Message Board > Main > General Questions Type I vs Type II error: can someone dumb this down Civilians call it a travesty.

Here the null hypothesis indicates that the product satisfies the customer's specifications. http://www.statisticshowto.com/type-i-and-type-ii-errors-definition-examples/ This standard is often set at 5% which is called the alpha level. Probability Of Type 1 Error 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. Type 1 Error Psychology A type I error means that not only has an innocent person been sent to jail but the truly guilty person has gone free.

Colors such as red, blue and green as well as black all qualify as "not white". navigate here In statistics the alternative hypothesis is the hypothesis the researchers wish to evaluate. Americans find type II errors disturbing but not as horrifying as type I errors. A data sample - This is the information evaluated in order to reach a conclusion. Type 1 Error Calculator

Obviously the police don't think the arrested person is innocent or they wouldn't arrest him. In the justice system, failure to reject the presumption of innocence gives the defendant a not guilty verdict. The null hypothesis - In the criminal justice system this is the presumption of innocence. http://clickcountr.com/type-1/type-1-error-vs-type-2-error-made-simple.html A jury sometimes makes an error and an innocent person goes to jail.

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. Types Of Errors In Measurement This means only that the standard for rejectinginnocence was not met. 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

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 If the null is rejected then logically the alternative hypothesis is accepted. 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. Power Of The Test In statistical hypothesis testing used for quality control in manufacturing, the type II error is considered worse than a type I.

However in both cases there are standards for how the data must be collected and for what is admissible. Type II errors: Sometimes, guilty people are set free.