# Type I error

Type I error (also known as an **error of the first kind**) occurs when a true null hypothesis is falsely rejected. Simply said, this type of error occurs when a difference is observed when in fact there is no difference after the test has been run.

When testing a hypothesis, we are testing the difference between two samples to determine if the difference is due to chance. The probability of a Type I error is the level of significance test of a hypothesis test. In most cases, significance level is denoted by alpha (α) and is set to 0.5 or 0.01. When testing the hypothesis, if the statistic tested ends up within the 95% or 99% range, we will accept the null hypothesis. If the tested statistic is outside of that range, the null hypothesis is rejected and the alternative is true. Because only a sample of individuals was used when testing our statistic, a decision has to be made about our hypothesis based on the parameters of the statistic being used. If the null hypothesis is true and we accept it, a correct decision has been reached. If the null hypothesis is true and is rejected, a type I error has occurred.

Null Hypothesis is true | Null Hypothesis is false | |
---|---|---|

Reject Null Hypothesis | Type I error | Correct Decision |

Fail to Reject Null Hypothesis | Correct Decision | Type II Error |

## See Also

## Reference

http://en.wikipedia.org/wiki/Type_I_and_type_II_errors

http://www.youtube.com/watch?v=FHT6e_mdGoU

http://www.stat.berkeley.edu/users/hhuang/STAT141/Lecture-FDR.pdf