Chi Square Distribution Graph. The chi square distribution is a special case of the gamma distribution and is one of the most widely used probability distributions in inferential statistics notably. The random variable for a chi square distribution with k degrees of freedom is the sum of k independent squared standard normal variables.
The chi square distribution s pdf curve is skewed to the right has a disproportionately long tail on the right side as shown in the above graph. This is the value of χ 2 that will give the specified p value for the chi square distribution. See a table of selected percentiles of the chi square distribution computed using the javascript calculation engine behind this page.
If you want to practice calculating chi square probabilities then use df n 1 d f n 1.
In probability theory and statistics the chi square distribution also chi squared or χ 2 distribution with k degrees of freedom is the distribution of a sum of the squares of k independent standard normal random variables. There is a different chi square curve for each df. As the number of degrees of freedom increases the graph of the chi square distribution looks more and more symmetrical. This is the value of χ 2 that will give the specified p value for the chi square distribution.
