A paired samples t-test is used to compare the means of two samples when each observation in one sample can be paired with an observation in the other sample.

The following step-by-step example shows how to perform a paired samples t-test to determine if the population means are equal between the following two groups:

Step 1: Calculate the Test Statistic

The test statistic of a paired t-test is calculated as:

t = x_diff / (s_diff/√n)

where:

• x_diff: sample mean of the differences
• s: sample standard deviation of the differences
• n: sample size (i.e. number of pairs)

We will calculate the mean of the differences between the two groups and the standard deviation of the differences between the two groups:

Thus, our test statistic can be calculated as:

• t = x_diff / (s_diff/√n)
• t = 1.75 / (1.422/√12)
• t = 4.26

Step 2: Calculate the Critical Value

Next, we need to find the critical value to compare our test statistic to.

For this example, we’ll use a two-tailed test with α = .05 and df = n-1 degrees of freedom.

According to the t-Distribution table, the critical value that corresponds to these values is 2.201:

Step 3: Reject or Fail to Reject the Null Hypothesis

Our paired samples t-test uses the following null and alternative hypothesis:

• H₀: μ₁ = μ₂ (the two population means are equal)
• H_A: μ₁ ≠ μ₂ (the two population means are not equal)

Since the absolute value of our test statistic (4.26) is greater than the critical value found in the t-table (2.201), we reject the null hypothesis.

This means we have sufficient evidence to say that the mean between the two groups is not equal.

Bonus: Feel free to use the Paired Samples t-test Calculator to confirm your results.