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Explain the meaning of type I error and type II error

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Explain the meaning of type I error and type II error.

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Contingency table for decision in hypothesis testing.

Actual condition/Decision Null hypothesis is true Null hypothesis is false
Reject the null hypothesis Wrong decision is taken (1) Correct decision is taken
Fail to reject the null hypothesis Right decision is taken Wrong decision is taken (2)

Type I

The incorrect decision being taken as (1) is the type I error from the above table. It is a situation when the assumption expressed as null is true, but the test decides to reject the assumption.

A type I error occurs when the sample is taken from an incorrect population.

Type II

The incorrect decision being taken as (2) is the type II error from the above table. It is a situation when the assumption expressed as null is false, but the test decides to fail to reject the assumption.

A type II error happens when the representative sample is quite small.