7Natural fault patterns, formed in response to a single tectonic event, often display significant 8 variation in their orientation distribution. The cause of this variation is the subject of some 9 debate: it could be 'noise' on underlying conjugate (or bimodal) fault patterns or it could be 10 intrinsic 'signal' from an underlying polymodal (e.g. quadrimodal) pattern. In this contribution, 11we present new statistical tests to assess the probability of a fault pattern having two (bimodal, 12 or conjugate) or four (quadrimodal) underlying modes. We use the eigenvalues of the 2 nd and 13 4 th rank orientation tensors, derived from the direction cosines of the poles to the fault planes, 14 as the basis for our tests. Using a combination of the existing fabric eigenvalue (or modified 15Flinn) plot and our new tests, we can discriminate reliably between bimodal (conjugate) and 16 quadrimodal fault patterns. We validate our tests using synthetic fault orientation datasets 17 constructed from multimodal Watson distributions, and then assess six natural fault datasets 18 from outcrops and earthquake focal plane solutions. We show that five out of six of these 19 natural datasets are probably quadrimodal. The tests have been implemented in the R language 20 and a link is given to the authors' source code. 21 22