# CHIINV

The CHIINV function returns the inverse of the right-tailed probability of the chi-squared distribution. This function is commonly used to test the goodness of fit of a statistical model. The function takes in two arguments, the probability and the degrees of freedom.

## Usage

Use the `CHIINV` formula with the syntax shown below, it has 2 required parameters:

Parameters:
1. probability (required):
The probability of the chi-squared distribution. Must be between 0 and 1.
2. degrees_freedom (required):
The degrees of freedom of the chi-squared distribution. Must be a positive integer.

## Examples

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

### Testing goodness of fit

When analyzing statistical data, it is often necessary to test the goodness of fit of the model. The CHIINV function can be used to calculate the critical value of a chi-squared test, which can be compared to the test statistic to determine if the model fits the data well.

### Calculating confidence intervals

The CHIINV function can also be used to calculate confidence intervals for the variance of a normal distribution. By calculating the upper and lower bounds of the confidence interval using the CHIINV function, you can estimate the range of values within which the true variance is likely to fall.

## Common Mistakes

`CHIINV` not working? Here are some common mistakes people make when using the `CHIINV` Google Sheets Formula:

### Using a probability value greater than 1 or less than 0

The probability value must be between 0 and 1. Check your input and adjust the value accordingly.

### Using a non-numeric value for probability or degrees_freedom

Both probability and degrees_freedom must be numeric values. Check your input and ensure that you are using numbers.

### Using a degrees_freedom value less than or equal to 0

The degrees_freedom value must be greater than 0. Check your input and adjust the value accordingly.

### Using a probability value that is not supported by the CHIINV function

The CHIINV function only accepts probability values between 0 and 1. Check your input and adjust the value accordingly.

### Using a degrees_freedom value that is too large

The CHIINV function can only handle degrees_freedom values up to a certain limit. Check your input and ensure that your degrees_freedom value is within the supported range.

The following functions are similar to `CHIINV` or are often used with it in a formula:

• `CHISQ.DIST`

The `CHISQ.DIST` function calculates the probability density function or the cumulative distribution function of a chi-squared distribution. This function is commonly used in hypothesis testing to determine the significance of the difference between expected and observed values. The output of this function can be used to make decisions about the null hypothesis.

• `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.

• `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.

You can learn more about the `CHIINV` Google Sheets function on Google Support.