# Type I Hypothesis Testing Error

(Redirected from Type I Error)

A Type I Hypothesis Testing Error is a hypothesis rejection decision that is a false positive prediction.

**Context:**- In Decision Theory, the Null Hypothesis is rejected when it is True.

**Example(s):**- ...

**Counter-Example(s):****See:**Null Hypothesis Testing, Family-Wise Error Rate.

## References

### 2015

- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/type_I_and_type_II_errors Retrieved:2015-1-20.
- In statistical hypothesis testing,
**type I and type II errors**are incorrect rejection of a true null hypothesis or failure to reject a false null hypothesis, respectively. More simply stated, a type I error is detecting an effect that is not present, while a type II error is failing to detect an effect that is present. The terms "type I error" and "type II error" are often used interchangeably with the general notion of false positives and false negatives in binary classification, such as medical testing, but narrowly speaking refer specifically to statistical hypothesis testing in the Neyman–Pearson framework, as discussed in this article.

- In statistical hypothesis testing,

### 2009

- (Wikipedia, 2009) ⇒ http://en.wikipedia.org/wiki/Type_I_and_type_II_errors
- Type I (α): reject the Null Hypothesis when the null hypothesis is true ...
- ...
- Type I error, also known as an "error of the first kind", an [math]α[/math] error, or a "false positive": the error of rejecting a null hypothesis when it is actually true. Plainly speaking, it occurs when we are observing a difference when in truth there is none. An example of this would be if a test shows that a woman is pregnant when in reality she is not. Type I error can be viewed as the error of excessive credulity.

- http://www.introductorystatistics.com/escout/main/Glossary.htm
- type I (hypothesis test) error The error of incorrectly rejecting a null hypothesis when it is true.