For the significance tests below, we will further assume that the errors are normally distributed.

This enables a significance test to be made for the validity of the model.

Such an approach may not always be available since it presupposes the practical availability of an appropriate significance test.

Naturally, any assumptions required for the significance test would carry over to the confidence intervals.

Some classical significance tests are not based on the likelihood.

For others it exemplifies the value of the likelihood principle and is an argument against significance tests.

A alternative significance test for this index has been developed for large samples.

Major organizations have not abandoned use of significance tests although some have discussed doing so.

The statistical data is not sufficiently large to enable satisfactory significance tests to be performed.

Statistical significance tests can help determine which patterns are meaningful.