# 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.

## Usage

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

Parameters:
1. x (required):
The observed F-ratio for which you want to find the probability.
2. degrees_freedom1 (required):
The numerator degrees of freedom.
3. degrees_freedom2 (required):
The denominator degrees of freedom.

## Examples

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

### Determine the significance of the difference between two variances

Suppose you have two data sets and you want to know if the difference between their variances is statistically significant. You can use the `F.DIST.RT` function to calculate the probability of obtaining an F-ratio as large as the one observed if the null hypothesis (that the variances are equal) is true. If the probability is less than your chosen significance level, you can reject the null hypothesis and conclude that the difference is significant.

### Calculate critical values for F-tests

The `F.DIST.RT` function can be used to find the critical value of an F-test for a given significance level and degrees of freedom. This is useful for determining the rejection region of an F-test and for calculating confidence intervals for the variance ratio.

## Common Mistakes

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

### Incorrect number of arguments

This error occurs when the formula is missing one or more required arguments or has extra arguments that are not needed. Check that the formula has the correct number of arguments and that they are in the correct order.

### Invalid input for x

This error occurs when the value for x is not a numeric value or is outside the allowable range. Check that the value for x is a valid number and within the allowable range.

### Invalid input for degrees_freedom1 or degrees_freedom2

This error occurs when the values for degrees_freedom1 or degrees_freedom2 are not numeric values or are negative. Check that the values for degrees_freedom1 and degrees_freedom2 are valid numbers and not negative.

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

• `F.DIST`

The F.DIST function calculates the cumulative distribution function (CDF) of the F-distribution. This function is commonly used in statistical analysis to determine the probability that two variances are from the same population. The result of F.DIST is the probability that the random variable of an F-distribution is less than or equal to a specified value.

• `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.

• `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.DIST`

The `T.DIST` function returns the probability of a Student's t-distribution with a specified degrees of freedom. This function is usually used in hypothesis testing to determine the probability that a sample mean is within a specified range of values.

• `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.

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