Although Excel has many built-in formulas that fall under many categories: statistical, mathematical, logical, and many more, there are some things that cannot be automatically calculated, but we have to do things manually.

Such is the case with **Mood’s Median Test**. This test is a **non-parametric statistical test** that is used to compare the medians of two or more independent samples. It is used mainly when the data that we have **does not meet the assumptions of parametric tests**, such as the t-test or ANOVA.

In the example below, we will show how this test can be performed in Excel.

## Mood’s Median Test in Excel

For our example, we will use two separate data sets, that will be located in **columns A and B**. They will show the **grades of students from class A and class B**:

Now we will take several steps for Mood’s Median test.

**Calculate MEDIAN**

The first thing that we need to do is to **calculate the medians for both classes**. We will insert the data in **columns C and D**. In **cell C2**, our formula will be:

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=MEDIAN(A3:A12) |

And we will calculate the **median for column B numbers in cell D2**. This is what we will end up with:

**Calculate Deviation**

For the second step, we calculate the absolute **difference between the two medians** by using the following formula (located in **cell E2**):

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=ABS(C2-D2) |

And will get **number 5**:

**Rank the data**

We need to rank our data, and the best way to do so is by using **RANK.EQ formula**. We will list all of our data in **column F**, and then will insert the formula:

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=RANK.EQ(F2,$F$2:$F$21) |

In **cell G2**, and will drag this formula till the end of the list:

**Sum of Ranks**

For the next thing, we need to **sum ranks for both classes**. As we are aware that the ranks for **class A are located in range G2:G11**, we will sum these cells and input them in **cell H2**. We will do the same thing for **class B**, and we will include the **range G12:G21**. The results will be **115 for class A**, and **89 for class B**, respectfully:

**Calculating Test Statistics**

In another cell, **cell J2**, we will calculate the test statistic using the following formula:

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=((H2-I2)^2)/(H2+I2) |

Which will look at the sum of ranks for **class A (cell H2)**, and the sum of ranks for **class B (cell I2)**. The result that we will get will be **3.31**:

**Compare to Critical Value**

We must look at the critical value from a **Chi-Squre distribution table** with **1 degree of freedom** and your chosen **significance level (for example, 0.05)**. The **critical importance might be around 3.841**.

**Interpretation of Results**

The result obtained from the Mood’s Median Test helps us determine whether there is a statistically significant difference between the medians of the two groups. In our case, the groups are Class A and Class B, and we are comparing their student grades. Here’s what the result could indicate based on the test statistic and the critical value:

**Null Hypothesis (H0):**There is**no significant difference**between the medians of the two groups (Class A and Class B).**Alternative Hypothesis (H1):**There**is a significant difference**between the medians of the two groups.

In our example, the **calculated test statistic (3.31)** **is smaller than the critical value (3.841)**. What this means to us is that **we do not have enough evidence** **to reject the null hypothesis**. Therefore, the final result based on the data that we have collected, is that **we cannot conclude a significant difference** in **medians between Class A and Class B at the chosen significance level**.

The example shown here is simplified, and any real-world analysis would mean that we will probably have to reconsider assumptions, data quality, and the context in which we are working. **Excel might not be the best tool for Mood’s Median Test**, and some other statistical tools can probably help us more.