Statistical Test

A test used to determine the statistical Significance of an observation. Two main types of error can occur:

1. A Type I Error occurs when a false negative result is obtained in terms of the Null Hypothesisby obtaining a false positive measurement.

2. A Type II Error occurs when a false positive result is obtained in terms of the Null Hypothesisby obtaining a false negative measurement.

Multiple-comparison corrections to statistical tests are used when several statistical tests are being performed simultaneously. For example, let's suppose you were measuring leg length in eight different lizard species and wanted to see whether theMeans of any pair were different. Now, there are pairwise comparisons possible, so even if all ofthe population means are equal, it's quite likely that at least one pair of sample means would differ significantly at the5% level. An Alpha Value of 0.05 is therefore appropriate for each individual comparison, but not for the set of all comparisons.

In order to avoid a lot of spurious positives, the Alpha Value therefore needs to be lowered to account for the numberof comparisons being performed. This is a correction for multiple comparisons. There are many different ways to dothis. The simplest, and the most conservative, is the Bonferroni Correction. In practice, more people are more willingto accept false positives (false rejection of Null Hypothesis) than false negatives (false acceptance of NullHypothesis), so less conservative comparisons are usually used.

• Plane-Filling Function
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