Below is the Bayesian network used in the BEST approach. We are assuming that the samples follow a Student's t-distribution. The segment and the benchmark have their ownand , but they share the same .
The default Confidence Level has been set to 95%. This is the same for the both tests.
As for the Bayesian test, the Region of Practical Equivalence (ROPE) on the Effect size around the null value has been set by default to [-0.1, 0.1].
The null value is declared to be rejected if the 95% Highest Density Interval (HDI) falls completely outside the ROPE.