### Using Independent samples t-test in Research

This easy tutorial will show you how to **run the Independent samples t-test in SPSS**, and how to interpret the result.

**The Independent Samples t-Test** compares the means of two independent groups in order to determine whether there is statistical evidence that the associated population means are significantly different. First of all, The Independent Samples

*t-Test*is a parametric test.

This test is also known as:

- Student
*t-Test* - Two-Sample
*t-Test* - Uncorrelated Scores
*t-Test* - Unpaired
*t-Test* - Unrelated
*t-Test*

The variables used in this test are known as:

- Dependent variable, or test variable
- Independent variable, or grouping variable (Source)

### An Example in SPSS: Independent samples t-test

Independent samples t-test uses to compare the mean value of a variable (for example, wage) measured in two different groups of people (for example, men and women) or different circumstances (for example, a union member or not a union member).

The independent-samples t-test evaluates the difference between the means of two independent or unrelated groups. That is, we evaluate whether the means for two independent groups are significantly different from each other.

Independent samples t-test examines whether there is a difference in the mean value between the two groups. Therefore, we need two variables to conduct independent samples t-test:

- one categorical variable with two groups (for example, male and female); independent variable
- one continuous variable (for example, annual wage), dependent variable.

*H*_{0}: µ_{1} – µ_{2} = 0 (“the difference between the two population means is equal to 0”)

*H*_{1}*: *µ_{1} – µ_{2} ≠ 0 (“the difference between the two population means is not 0”)

To show how to run the **independent samples t-test in SPSS.** We will use one categorical variable (gender) with two groups (male and female), and one continuous variable (wage – annual wage in dollars).

This easy tutorial will show you **how to run Independent samples t-test**, and how to interpret the result.