Assessment |
Biopsychology |
Comparative |
Cognitive |
Developmental |
Language |
Individual differences |
Personality |
Philosophy |
Social |

Methods |
Statistics |
Clinical |
Educational |
Industrial |
Professional items |
World psychology |

**Statistics:**
Scientific method ·
Research methods ·
Experimental design ·
Undergraduate statistics courses ·
Statistical tests ·
Game theory ·
Decision theory

## Probability of error in hypothesis testing[edit | edit source]

In hypothesis testing in statistics, two types of *error* are distinguished.

- Type I errors which consist of rejecting a null hypothesis that is true; this amounts to a false positive result.
- Type II errors which consist of failing to reject a null hypothesis that is false; this amounts to a false negative result.

The **probability of error** is similarly distinguished.

- For a Type I error, it is shown as α (alpha) and is known as the
*size*of the test and is 1 minus the specificity of the test. It should also be noted that α (alpha) is sometimes referred to as the confidence of the test, or the level of significance (LOS) of the test. - For a Type II error, it is shown as β (beta) and is 1 minus the power or 1 minus the sensitivity of the test.

## Probability of error in statistical modelling and econometrics[edit | edit source]

Many models in statistics and econometrics will usually seek to minimise the difference between observed and predicted or theoretical values. This difference is known as an *error*, though when observed it would be better described as a *residual*.

The error is taken to be a random variable and as such has a probability distribution.

- de:Irrtumswahrscheinlichkeit

This page uses Creative Commons Licensed content from Wikipedia (view authors). |