 # HOW TO RUN PAIRED SAMPLE T TEST IN SPSS

## What is the Paired Sample T-Test?

### Using Paired Sample T-Test in Research

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

The Paired Samples t-Test compares two means that are from the same individual, object, or related units.

The two means can represent things like:

• A measurement taken at two different times (e.g., pre-test and post-test with an intervention administered between the two-time points)
• A measurement taken under two different conditions (e.g., completing a test under a “control” condition and an “experimental” condition)
• Measurements are taken from two halves or sides of a subject or experimental unit (e.g., measuring hearing loss in a subject’s left and right ears). (Source)

We use the Paired samples t-test when we have only one group of subjects. However, we collect data from them at two different time intervals or under two different conditions (for example, we measure test results before and after training). That’s to say, The related t-test indicates whether there are statistically significant differences in the mean of the results obtained at time 1 and at time 2 or before and after an event (for example, training).

### Assumptions of the Dependent T-Test:

When performing a Paired t-Test procedure the following assumptions are required:

• The dependent variable must be continuous (interval/ratio).
• The observations are independent of one another.
• The dependent variable should be approximately normally distributed.
• The dependent variable should not contain any outliers

### An Example: Paired T-Test

This guide will explain, step by step, how to run Paired T-Test in SPSS statistical software by using an example.

We will examine whether the training influenced on the Math test score. Therefore, we measured the results on the Math test before the training, then the student had the training, and we measured the results on the Math test after the training. Finally, we have two variables Math Test score 1 and Math Test score2.

Null hypothesis:

There is not a difference between mean at time 1 and time 2 (or before and after an intervention).

Alternative hypothesis:

There is a difference between mean at time 1 and time 2 (or before and after an intervention).

This easy tutorial will show you how to run the Paired SampleT Test in SPSS, and how to interpret the result.

## How to report a Paired Sample T Test results: Explanation Step by Step

### How to Report Descriptive Statistics Table in SPSS Output?

The first table in the output window shows descriptive statistics of the variables (mean, standard deviation, standard error mean, and the number of observations).

The average Math test score before training was 73.08 (M=73.08; SD=16.89), and the average Math test score after training was 68.83 (M=68.83; SD=17.69).

### How to Report Paired Samples Table in SPSS Output?

The second table shows the correlations between Math scores before and after the training.

The correlation coefficient shows that there is a non-significant positive relationship between math score before the training and math score after the training, [r(37) = .058, p = .735].

### How to Report P-Value in Paired Sample Table SPSS Output?

The third table shows the results of the paired samples t-test. We should look at the significance of test statistics (last column).

If the p-value is lower than .05 then, we reject the null hypothesis. So, we conclude that there is a difference between the mean before and after the intervention.

In our example, p = .284 > .05, so we fail to reject the null hypothesis and conclude that there is no difference between the math test score before and the math test score after the training.

## How to Interpret a Paired Sample T-Test Results in APA Style?

A Paired samples t-test was conducted to determine the effect of training on a math test score. The results indicate a not significant difference between math test score before training (M=73.08; SD=16.89) and Math test score after training (M=68.83; SD=17.69); [t(36) = 1.086, p = .284].

The 95% confidence interval of the difference between the means ranged from [-3.68 to 12.16] and did not indicate a difference between the means of the samples. We, therefore, fail to reject the null hypothesis that there is no difference between the means and conclude that there is not an effect of training on a math test score.

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