When you conduct a Chi-Square test, you will get a test statistic as a result. To determine if the results of the Chi-Square test are statistically significant, you can compare the test statistic to a** Chi-Square critical value**. If the test statistic is greater than the Chi-Square critical value, then the results of the test are statistically significant.

The Chi-Square critical value can be found by using a Chi-Square distribution table or by using statistical software.

To find the Chi-Square critical value, you need:

- A significance level (common choices are 0.01, 0.05, and 0.10)
- Degrees of freedom

Using these two values, you can determine the Chi-Square value to be compared with the test statistic.

**How to Find the Chi-Square Critical Value in Excel**

To find the Chi-Square critical value in Excel, you can use the** CHISQ.INV.RT()** function, which uses the following syntax:

**CHISQ.INV.RT**(probability, deg_freedom)

**probability:**The significance level to use**deg_freedom**: The degrees of freedom

This function returns the critical value from the Chi-Square distribution based on the significance level and the degrees of freedom provided.

For example, suppose we would like to find the Chi-square critical value for a significance level of 0.05 and degrees of freedom = 11.

In Excel, we can type the following formula: **CHISQ.INV.RT(0.05, 11)**

This returns the value **19.67514**. This is the critical value for a significance level of 0.05 and degrees of freedom = 11.

Note that this also matches the number we would find in the Chi-Square distribution table with α = 0.05, DF *(degrees of freedom)* = 11.

**Cautions on Finding the Chi-Square Critical Value in Excel**

Note that the** CHISQ.INV.RT()** function in Excel will throw an error if any of the following occur:

- If any argument is non-numeric.
- If the value for
*probability*is less than zero or greater than 1. - If the value for
*deg_freedom*