# CHISQ.INV.RT

The `CHISQ.INV.RT` function returns the inverse of the right-tailed probability of the chi-squared distribution. It is commonly used in hypothesis testing and goodness-of-fit analysis to determine whether an observed set of data is significantly different from a theoretical distribution. The function takes two arguments: the probability and the degrees of freedom.

## Usage

Use the `CHISQ.INV.RT` formula with the syntax shown below, it has 2 required parameters:

Parameters:
1. probability (required):
The probability of the chi-squared distribution in the right-tail. Must be a decimal between 0 and 1, inclusive.
2. degrees_freedom (required):
The degrees of freedom of the chi-squared distribution. Must be an integer greater than or equal to 1.

## Examples

Here are a few example use cases that explain how to use the `CHISQ.INV.RT` formula in Google Sheets.

### Testing for independence in categorical data

In a chi-squared test for independence, the `CHISQ.INV.RT` function can be used to determine the critical value for rejecting the null hypothesis that two categorical variables are independent. For example, if we want to test whether there is a relationship between gender and voting preference, we can use the function to calculate the critical value for a given significance level and degrees of freedom.

### Goodness-of-fit test

The `CHISQ.INV.RT` function can also be used in a goodness-of-fit test to determine whether an observed set of data fits a theoretical distribution. For example, if we want to test whether a set of dice rolls follows a uniform distribution, we can use the function to calculate the critical value for a given significance level and degrees of freedom.

## Common Mistakes

`CHISQ.INV.RT` not working? Here are some common mistakes people make when using the `CHISQ.INV.RT` Google Sheets Formula:

### Missing arguments

One or both of the required arguments are missing. Make sure to include both the probability and degrees_freedom arguments.

### Invalid probability

The probability argument should be a decimal number between 0 and 1. Double-check that you have entered a valid probability value.

### Invalid degrees of freedom

The degrees_freedom argument should be a positive integer. Double-check that you have entered a valid degrees of freedom value.

### Incorrect order of arguments

Make sure to enter the probability argument first and the degrees_freedom argument second.

The following functions are similar to `CHISQ.INV.RT` or are often used with it in a formula:

• `CHISQ.INV`

The CHISQ.INV function returns the inverse of the right-tailed probability of the chi-squared distribution. It is commonly used in hypothesis testing where the null hypothesis is that the observed data follows a chi-squared distribution. The function returns the value of the chi-squared random variable at which the cumulative distribution function equals the given probability. This function is useful for finding critical values after performing a chi-squared test.

• `CHISQ.DIST.RT`

The `CHISQ.DIST.RT` function returns the right-tailed probability of the chi-squared distribution. This function is commonly used in hypothesis testing and to calculate confidence intervals for the variance of a normal distribution. The chi-squared distribution is often used in goodness-of-fit tests and tests of independence in contingency tables.

• `CHISQ.TEST`

The `CHISQ.TEST` formula calculates the test for independence of two categorical ranges of data using the chi-squared distribution. It returns the probability that any observed differences between the two ranges are due to chance. This formula is commonly used in hypothesis testing to determine whether there is a significant association between two variables.

• `T.INV.2T`

The `T.INV.2T` function returns the two-tailed inverse of the t-distribution. This is commonly used in hypothesis testing to determine the critical value of t for a given level of significance and degrees of freedom.

• `F.INV.RT`

The `F.INV.RT` function returns the inverse of the F probability distribution. It is commonly used in hypothesis testing to determine the critical value at which the null hypothesis can be rejected. The function takes three arguments: the probability value, and the two degrees of freedom values.

You can learn more about the `CHISQ.INV.RT` Google Sheets function on Google Support.