# 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.

## Usage

Use the `F.INV.RT` formula with the syntax shown below, it has 3 required parameters:

Parameters:
1. probability (required):
The probability value between 0 and 1 for which you want to find the inverse of the F probability distribution.
2. degrees_freedom1 (required):
The numerator degrees of freedom value.
3. degrees_freedom2 (required):
The denominator degrees of freedom value.

## Examples

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

### Critical value determination

Suppose you have a data set and you want to test whether two population variances are equal. You could use the `F.TEST` function to calculate the F statistic, and then use the `F.INV.RT` function to determine the critical value for a given level of significance and degrees of freedom. If the calculated F statistic is greater than the critical value, you can reject the null hypothesis that the variances are equal.

### Regression analysis

In regression analysis, the `F.INV.RT` function can be used to calculate the F statistic for the overall significance of a regression model. The function can also be used to calculate the critical value for a given level of significance and degrees of freedom.

### ANOVA

In ANOVA (Analysis of Variance), the `F.INV.RT` function can be used to calculate the critical value for a given level of significance and degrees of freedom. This can be used to test the null hypothesis that the means of multiple groups are equal.

## Common Mistakes

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

### Incorrect probability input

Users often input a probability value that is outside the range of 0 and 1. This formula requires a probability value between 0 and 1.

### Incorrect degrees of freedom input

Users sometimes input the degrees of freedom values in the wrong order or input non-numeric values. This formula requires two numeric values for degrees of freedom, with the first value being greater than 0.

### Incorrect formula name

Users sometimes misspell the formula name or confuse it with similar formulas. This formula is called F.INV.RT in Google Sheets.

### Missing arguments

Users sometimes forget to input all three required arguments. This formula requires a probability value, and two degrees of freedom values.

### Incorrect cell references

Users sometimes reference the wrong cells or ranges for the input arguments. Double-check the cell references to ensure they are correct.

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

• `F.DIST.RT`

The `F.DIST.RT` function calculates the right-tailed F probability distribution. It returns the probability that the observed F-ratio is greater than the critical value for a given degrees of freedom. This function is commonly used in hypothesis testing to determine the significance of the difference between the variances of two data sets.

• `F.TEST`

The `F.TEST` function returns the result of an F-test, which tests the equality of variances between two datasets. It is commonly used to compare the variances of two datasets to determine if they are significantly different. If the result is less than or equal to a critical value, the variances are considered equal. If the result is greater than the critical value, the variances are considered unequal.

• `T.INV`

The `T.INV` function returns the inverse of the Student's t-distribution for the provided probability and degrees of freedom. This function is commonly used to calculate a critical value from the t-distribution when working with small sample sizes.

• `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.

## Learn More

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