**2.1 Calculating a G ratio**

The G test can be run as a one-sided test upper-limit test, as a one-sided lower-limit test and as a two-sided test at any significance level α. When running a G test, it is checked for each data set j if the corresponding inequality is met:

One-sided upper limit test: G

_{j}< G_{UL}(α,ν_{j},ν_{total},L)
One-sided lower limit test: G

_{LL}(α,ν_{j},ν_{total},L) < G_{j}
Two-sided test: G

_{LL}(α/2,ν_{j},ν_{total},L) < G_{j }< G_{UL}(α/2,ν_{j},ν_{total},L)**2.3 Computing critical G values**

The critical G values G

_{UL}and G_{LL}are calculated from:
The equations to calculate G

_{UL}and G_{LL}are exact. The accuracy of G_{UL}and G_{LL}only depends on the accuracy of the input value F_{c}. F_{c}can be read from tables, but can also be obtained using the FINV function in Excel: F_{c}= FINV(probability, degrees of freedom 1, degrees of freedom 2).**2.4 Evaluating balanced and unbalanced designs**

The G test can handle both balanced and unbalanced designs. In case of balanced designs, all data sets have the same number of degrees of freedom. Balanced designs are covered in § 3, unbalanced designs in § 4.

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