# Difference Between One-Tailed and Two-Tailed Tests

• Last Updated : 06 Jul, 2022

One and Two-Tailed Tests are ways to identify the relationship between the statistical variables. For checking the relationship between variables in a single direction (Left or Right direction), we use a one-tailed test. A two-tailed test is used for checking whether the relations between variables are in any direction or not.

### One-Tailed Test

A one-tailed test is based on a uni-directional hypothesis where the area of rejection is on only one side of the sampling distribution. It determines whether a particular population parameter is larger or smaller than the predefined parameter. It uses one single critical value to test the data.

Example: Effect of participants of students in coding competition on their fear level.

• H0: There is no important effect of students in coding competition on their fear level.

The main intention is to check the decreased fear level when students participate in a coding competition.

### Two-Tailed Test

A two-tailed test is also called a nondirectional hypothesis. For checking whether the sample is greater or less than a range of values, we use the two-tailed. It is used for null hypothesis testing.

Example: Effect of new bill pass on the loan of farmers.

• H0: There is no significant effect of the new bill passed on loans of farmers.

New bill passes can affect in both ways either increase or decrease the loan of farmers.

Difference Between One and Two-Tailed Test:

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