A number of parametric and non-parametric statistical tests can be used to determine if identified spatial relationships are considered statistically significant.

Data logs of all functional and parametric tests shall be collated for further analysis.

If the summed responses fulfill these assumptions, parametric statistical tests such as the analysis of variance can be applied.

Log-transformation of data before the application of parametric test, or the use of non-parametric statistics is recommended by several authors.

The parametric test assumes that the errors have a normal distribution.

Variables with normal distribution and homogeneous variance were compared by means of parametric tests, otherwise their non-parametric counterparts were used.

Both parametric and non-parametric tests were used because the distributional assumptions required for parametric testing may not be satisfied in all cases.

You cannot use a parametric test because the size-frequency of the potential prey population is unlikely to be normal.

Exceptions when it is certain that parametric tests are exact include tests based on the binomial or Poisson distributions.

This suggests that standard parametric statistical tests are appropriate for subsequent analysis.