When the random variable is chi square distribution with degrees of freedom.
2.
G 2 approximately follows a chi square distribution, especially with larger samples.
3.
With increasing dfs the fit decreases but much more slowly than the chi square distribution.
4.
The chi square distribution for " k " degrees of freedom will then be given by:
5.
The fit of chi square distribution depends on the degrees of freedom ( df ) with good agreement with df = 1 and decreasing agreement as the df increases.
6.
This result is used to justify using a normal distribution, or a chi square distribution ( depending on how the test statistic is calculated ), when conducting a hypothesis test.
7.
In the case of a unimodal variate the ratio of the jackknife variance to the sample variance tends to be distributed as one half the square of a chi square distribution with two degrees of freedom.
8.
To test for deviations from this value he proposed testing its value against the chi square distribution with " n " degrees of freedom where " n " is the number of sample units.
9.
The chi square test gives only a rough indication about the existence of gross errors, and it is easy to conduct : one only has to compare the value of the objective function with the critical value of the chi square distribution.
10.
Where } } is the percentile of the chi squared distribution with " v " degrees of freedom, n is the number of observations of inter-arrival times in the sample, and x-bar is the sample average.
