The correct answer is: variance.
The variance of a chi-squared distribution is twice the degrees of freedom. This is because the chi-squared distribution is a scaled version of the gamma distribution, and the variance of a gamma distribution is equal to its degrees of freedom multiplied by its scale parameter.
The variance of a random variable is a measure of how spread out its values are. A low variance indicates that the values are clustered close to the mean, while a high variance indicates that the values are spread out over a wider range.
The degrees of freedom of a chi-squared distribution are the number of independent pieces of information that are used to calculate the chi-squared statistic. For example, if you have a sample of 10 data points and you are calculating the chi-squared statistic for a goodness-of-fit test, then the degrees of freedom would be 9.
The mode of a distribution is the value that occurs most often in the distribution. The mode of a chi-squared distribution is not defined, because there is no value that occurs more often than any other.
In conclusion, the variance of a chi-squared distribution is twice the degrees of freedom. This is because the chi-squared distribution is a scaled version of the gamma distribution, and the variance of a gamma distribution is equal to its degrees of freedom multiplied by its scale parameter.