The CHISQ.INV.RT function returns the inverse of the right-tailed probability of the chi-squared distribution. It is used in statistics to find critical values for the chi-squared distribution.


=CHISQ.INV.RT(probability, degrees_freedom)

probability The probability of the chi-squared distribution.
degrees_freedom The degrees of freedom for the chi-squared distribution.


When dealing with statistical analysis and the chi-squared distribution, the CHISQ.INV.RT function in Excel proves its worth by providing the critical value for a given right-tailed probability. This critical value is essential in hypothesis testing, goodness-of-fit tests, and other statistical procedures involving the chi-squared distribution. By leveraging the CHISQ.INV.RT function, analysts can ascertain the upper threshold beyond which the observed data would be deemed statistically significant, based on a specified probability and degrees of freedom. This insight aids in drawing conclusions regarding the validity of statistical hypotheses and the fit of empirical data to theoretical distributions.


Suppose you want to find the critical value for a chi-squared distribution with 5 degrees of freedom at a right-tailed probability of 0.05. The CHISQ.INV.RT formula would be: =CHISQ.INV.RT(0.05, 5)

In a statistical experiment with 8 degrees of freedom, you need to determine the critical value corresponding to a right-tailed probability of 0.01. You would apply the CHISQ.INV.RT function as follows: =CHISQ.INV.RT(0.01, 8)


What is the significance of the critical value derived from the CHISQ.INV.RT function?

The critical value obtained from the CHISQ.INV.RT function serves as the upper boundary for a given right-tailed probability in the chi-squared distribution. It aids in evaluating the statistical significance of observed data and supports decision-making in hypothesis testing or goodness-of-fit assessments.

Can the CHISQ.INV.RT function be used to find critical values for different levels of significance?

Yes, the CHISQ.INV.RT function is flexible and can be utilized to obtain critical values for various levels of significance by inputting different right-tailed probabilities. This empowers analysts to tailor the critical value calculations to meet the specific requirements of their statistical analyses.

Are there any restrictions on the degrees of freedom for the CHISQ.INV.RT function?

The degrees of freedom used in the CHISQ.INV.RT function must be non-negative integer values, as they represent the number of independent variables in the chi-squared distribution. It’s important to ensure that the degrees of freedom align with the statistical context in which the function is applied.

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