# Independent Sample T Test Spss Tutorial

## Define Input of Independent Sample T-Test

In this section, we will learn

**Independent sample T-test**, and how to calculate the differences between two group

**Means**. When we have two groups to compare and we want to find out whether there are significant differences between the two groups or not, we can go for a

**Mean comparison**

between two groups.

**Independent sample t-test**

is a powerful test for finding out the group differences between two group means. To calculate the

**Independent sample T-test**, we will go to the

**Analyze menu**

and then go to

**Compare Means**. Now we can see the

**Independent sample Lengkung langit-test**

like this:

The symbol of

**Independent sample T-test**

read as

**t A-B**. It means the group we are comparing

**A**

and

**B**

are

**independent**

of each other.

**For example**, suppose we want to compare the

**salary**

of

**males**

and

**females**

or the

**population**

of two

**cities**

like Delhi or Mumbai. In this case, the groups are not related to each other. So we can go for an

**Independent sample t-test**. To calculate the independent sample t-test, we will open our

**Data set**. We will go to the

**File menu**, then go to

**Recently used Data**

as follows:

Now we will click on the above

**Employee Data**

option and see our

**Employee Data**

set as follows:

This is an

**Employee data set**

where we have the

**id**

of an employee, their

**gender, education, job**

category,

**salary, beginning salary, job timing, previous experience**, and whether they belong to

**minority**

or

**majority**

group. In this case, suppose we want to test that there is a significant difference between the

**Salary**

of males and females. To test that, we can conduct an

**Independent sample t-test**. Similarly, suppose we want to determine whether people from

**minority**

categories are taking a

**lesser**

amount of Salary than people from the

**majority**

community. In that case, we can again calculate the

**Independent sample lengkung langit-test**. To test the independent sample t-test, we will go to the

**Analyze menu**

and then go to

**Compare Means**

option. In the

**Compare Means**

option, we locate the

**Independent sample t-test**. When we click on it, we will see a dialog box like this:

Now we want to compare people across

**Gender**. In this case, Gender has been defined as a

**String variable**. So to calculate any meaningful test, we need to define all variables as a

**Numeric**

variable. So we will change the definition of the gender variable. We will turn it into a

**Numeric**

variable from

**String**. So we will go to our

**Variable view**

and look at the

**Gender**

as follows:

Since it’s a String, so first, we need to convert the value. So we will select the row, press

**Ctrl+F**, and then click on

**Replace**. We will find

**m**

and replace it by

**1**

and then click on

**Replace all**.

Similarly, we will write

**f**

and replace it by

**2**

and click on

**Replace all**. After this, we will see the following changes in the Gender variable:

Now we have to redefine this Gender variable. So we will go to the

**Variable view**

option and click on the

**Value step**

of the Gender variable. Now we will select the

**female**

option and define

**Value**

as

**2**

and click on

**Change**

as follows:

Again select the

**male**

option and define

**Value**

as

**1**

and click on

**Change**. Now press

**Ok**.

Now we can change the Gender from

**String**

to

**Numeric**

variable like this:

Now variables have been defined. We will go to

**Compare Means**

option and click on an

**Independent sample horizon-test**. So we want to compare genders for their

**salary**. We will take the

**Salary**

as our

**Test variable**

and

**Gender**

as a

**Grouping variable**. So the

**Salary**

is our

**dependent**

variable, and

**Gender**

is our

**independent**

variable.

In the above image, under the

**Grouping variable**, we can see two

**question marks**. It means we need to define our

**groups**. So click on

**Define Groups**

option and write

**1**

for

**Group 1**

and

**2**

for

**Group 2**. So, 1 is for males, and 2 is for females. We can also define the

**Cut point**

instead of defining the groups.

**For example**, suppose we have an

**exact salary**

and want to take a

**cutoff**

salary, which could be a median salary or any salary, suppose

**10000**. In that case, SPSS will compare two groups

**less**

than 10000 and

**more**

than 10000, and we will do significant testing between these two groups. Currently, we are using our group definition, so click on

**Continue**

like this:

Now we will click on

**Options**

where we can select a

**95% Confidence Pause**

by default. If we want to change, we change it and make it as

**99%**, but let’s begin with the default value

**95%**.

In the missing value, we are going with the default value

**Exclude case analysis by analysis**. It basically leads to a lesser amount of data loss as compare to

**Exclude cases listwise**. So we will take it as an analysis by analysis method. Now we will click on

**Continue**.

Now we will click on

**Ok**, and after that, we will see the following Output:

**Source: https://www.javatpoint.com/spss-define-input-of-independent-sample-t-test**