 # Reporting Independent T Test in SPSS

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## How to Run Independent Samples t Test in SPSS: Explanation Step by Step

### A new window with variables in the left box will open.

#### STEP 3

Using an arrow or double click on the variable, transfer variable wage to the Test Variable(s) box. In the same way transfer variable gender to the Grouping Variable box.

### Right-click on the variable gender in the Grouping Variable box to see how variable is coded. Click on Variable information and the new box will open to show how the variable is coded.

#### STEP 5

Click on Define groups option below Grouping variable box. Enter the variable codes (0 and 1). Click Continue and then OK.

## How to report Independent T Test results: Explanation Step by Step

### How to Report Group Statistic Table in SPSS Output?

The first table Group Statistics shows mean, standard deviation, and standard error mean for each group

### How to Report Independent samples t-test Table in SPSS Output?

The second table Independent samples test shows the results of independent samples t-test.

If the p-value (column sig. in column Levene’s test for equality of variances) is higher than 0.05, for the reason that we conclude that equal variances assume and use the first row of the table t-test for equality of means to conclude.

Since the p-value in our example is .605, we assume that variances are equal and use the first row of the table t-test for equality of means to make a conclusion.

## How to Interpret an Independent Samples t-Test Results in APA Style?

An independent-samples t-test was conducted to determine whether there is a difference in annual wages between males and females. The results indicate a not significant difference between male (M=28249.31, SD=12697.09) and female (M=32875.05, SD=13583.47), [t(46) = -1.218, p = .229 > .05]. The 95% confidence interval of the difference between means ranged from [-12269.716 to 3018.241] and did not indicate a difference between the means of the sample. Consequently, we fail to reject the null hypothesis that there is no difference between the sample means.

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