This article describes the **independent t-test formula**, which is used to compare the means of two independent groups. The independent t-test formula is also referred as:

*unpaired t-test formula*,*independent samples t-test formula*,*two sample t-test formula*,*2 sample t-test formula*and*two sample t-test equation*

The independent samples t-test comes in two different forms:

- the standard
*Student’s t-test*, which assumes that the variance of the two groups are equal. - the
*Welch’s t-test*, which is less restrictive compared to the original Student’s test. This is the test where you do not assume that the variance is the same in the two groups, which results in the fractional degrees of freedom.

In this article, you will learn the *Student t-test formula* and the *Weltch t-test formula*.

Contents:

#### Related Book

Practical Statistics in R II - Comparing Groups: Numerical Variables## Formula

**Classical two independent samples t-test**(Student t-test). If the variance of the two groups are equivalent (**homoscedasticity**), the t-test value, comparing the two samples (\(A\) and \(B\)), can be calculated as follow.

\[

t = \frac{m_A - m_B}{\sqrt{ \frac{S^2}{n_A} + \frac{S^2}{n_B} }}

\]

where,

- \(m_A\) and \(m_B\) represent the mean value of the group A and B, respectively.
- \(n_A\) and \(n_B\) represent the sizes of the group A and B, respectively.
- \(S^2\) is an estimator of the pooled variance of the two groups. It can be calculated as follow :

\[

S^2 = \frac{\sum{(x-m_A)^2}+\sum{(x-m_B)^2}}{n_A+n_B-2}

\]

with degrees of freedom (df): \(df = n_A + n_B - 2\).

**Welch t-statistic**. If the variances of the two groups being compared are different (**heteroscedasticity**), it’s possible to use the Welch t-test, which is an adaptation of the Student t-test. The Welch t-statistic is calculated as follow :

\[

t = \frac{m_A - m_B}{\sqrt{ \frac{S_A^2}{n_A} + \frac{S_B^2}{n_B} }}

\]

where, \(S_A\) and \(S_B\) are the standard deviation of the the two groups A and B, respectively.

Unlike the classic Student’s t-test, the Welch t-test formula involves the variance of each of the two groups (\(S_A^2\) and \(S_B^2\)) being compared. In other words, it does not use the pooled variance \(S\).

The **degrees of freedom** of **Welch t-test** is estimated as follow :

\[

df = (\frac{S_A^2}{n_A}+ \frac{S_B^2}{n_B})^2 / (\frac{S_A^4}{n_A^2(n_A-1)} + \frac{S_B^4}{n_B^2(n_B-1)} )

\]

A p-value can be computed for the corresponding absolute value of t-statistic (|t|).

If the p-value is inferior or equal to the significance level 0.05, we can reject the null hypothesis and accept the alternative hypothesis. In other words, we can conclude that the mean values of group A and B are significantly different.

Note that, the Welch t-test is considered as the safer one. Usually, the results of the **classical student’s t-test** and the **Welch t-test** are very similar unless both the group sizes and the standard deviations are very different.

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