Enter the mean difference score, hypothesized population mean difference, standard deviation of the difference scores, and total number of pairs into the calculator to determine the t-value.

## Dependent T-Test Formula

The following formula is used to calculate the t-value in a dependent t-test.

t = (M - μ) / (s / √n)

Variables:

• t is the t-value M is the mean difference score μ is the hypothesized population mean difference (usually 0) s is the standard deviation of the difference scores n is the total number of pairs

To calculate the t-value, subtract the hypothesized population mean difference from the mean difference score. Then, divide the standard deviation of the difference scores by the square root of the total number of pairs. Finally, divide the first result by the second result to get the t-value.

## What is a Dependent T-Test?

A Dependent T-Test, also known as a paired sample T-Test, is a statistical procedure used to determine whether the mean difference between two sets of observations is zero. It is used when the observations are dependent; that is, when there is a meaningful relationship between the two sets of data, such as a before-and-after scenario or when the same subjects are measured more than once under different conditions.

## How to Calculate Dependent T-Test?

The following steps outline how to calculate a Dependent T-Test using the formula: t = (M – μ) / (s / √n).

1. First, determine the mean difference score (M).
2. Next, determine the hypothesized population mean difference (μ). This is usually 0 unless stated otherwise.
3. Next, determine the standard deviation of the difference scores (s).
4. Next, determine the total number of pairs (n).
5. Finally, calculate the t-value using the formula t = (M – μ) / (s / √n).
6. After inserting the variables and calculating the result, check your answer with a statistical calculator or software.

Example Problem:

Use the following variables as an example problem to test your knowledge:

Mean difference score (M) = 2.5

Hypothesized population mean difference (μ) = 0

Standard deviation of the difference scores (s) = 1.2

Total number of pairs (n) = 30