# free F distribution calculator with graph generator

## Critical Value Calculator

Our free online test statistics calculator allows you to find the result of the f-value from the F distribution.

You can specify the significance level and the degrees of freedom for the numerator and denominator (1 and 2). Select the left or the right tail depending on the test you want to perform.

In addition to the result, you will get a graph that you can download thanks to our graph generator system which reflects the F distribution.

### Critical value result

## P-value Calculator

To get the p-value of the F distribution, use our online statistical calculator.

You only need to define the F-value and the degree of freedom 1 y 2 corresponding to the numerator and denominator.

You may receive the graph produced by our graph generator and download it in addition to the p-value result.

### P-value result

## Frequently asked questions about the F-distribution

We will try to answer the most frequently asked questions about the f distribution in this section. We will cover the basics of the F-distribution to give you a fundamental and complementary understanding. We will try to provide you with relevant information on frequently asked questions.

### Questions about the F-distribution

The F-distribution formula, used in our online F-distribution calculator, in regard to the probability density function (pdf):

Where: the degrees of freedom are d1 and d2, and the beta function is Β.

F-distribution, alternatively known as the Fisher–Snedecor distribution, it is a probability distribution related to statistical inference, particularly in the analysis of the variances of two different populations or samples. It is a statistical technique that helps us determine whether or not there are significant differences between different samples. The F-distribution is used when one seeks to study the ratio of the variances of two normally distributed populations. The F-distribution has two parameters that are the degrees of freedom: one for the numerator and one for the denominator (you can try our F-distribution calculator to get the result).

Snedecor's F-distribution is a technique that has wide applications in statistical inference, where it is used to compare the variances of two different or independent populations that follow a normal distribution.

The most important assumption to keep in mind is that the samples must be drawn from populations that follow a normal distribution. If the data in an experiment comes from a normally distributed population, the results will be more accurate.

The F distribution has certain properties that differentiate it, the same happens with the other distributions.

The curve is not symmetric, but is skewed to the right. There is a different curve for each set of degrees of freedom. The value of the F-distribution is never less than zero, the distribution does not have a tail that reaches infinity on the left, as occurs, for example, with the normal distribution. As the degrees of freedom of the numerator and denominator increase, their skewness decreases (use our **F distribution calculator**, select the critical value or the p value and fill in the corresponding fields and you will obtain a graph that reflects this property).

The normal distribution is used when the variances are known and the sample size is large, determining whether or not the population means differ. To investigate the variations of two populations, the F distribution is used. In the case of the normal distribution, the data is bell-shaped, the mean, median, and mode are equal, and the normal distribution is symmetric about the mean. The curve of the F distribution is usually skewed to the right rather than being symmetric. Unlike the normal distribution, the F distribution does not contain a left tail that extends to infinity.

Student's t-distribution is commonly used to estimate the mean of a normal distribution when the sample size is less than 30 and the population standard deviation is unknown. As for the Fisher–Snedecor distribution, it is used to estimate the ratio of the variances of two normal distributions.