)
difference between 1:1 input and output
Chapter xxx outlined an experimental procedure for predicting the precision of the the splitting test, and particularly the magnitude of change in surface strain which is associated with the arbitrary angle of the cut during the splitting test. Experimentally the correlation between the two quartering tests \(\left(0.89\right)\) and the estimated standard deviation of the difference distribution \(\left(300\ \mu\epsilon\right)\). When the experimental method is  compared to the closest theoretical example (Figure xxx), it is seen that the experimental results both must exist when COpposing is grater than \(0\) and CAdjoining is greater than \(-0.5\). When ---entwhistle 2010--- is repeated within the theoretical framework (Figure xxx) a similar conclusion can be drawn, however slightly negative COpposing and high  CAdjoining populations could also be included. Following this, two population sets will be refereed to, the full population set consisting off all of the populations used to make the above figures, and the limited population set, the set which exists inside the lower bounds suggested by the experimental work in Chapter xxx.
When perpendicular splitting test results are compared it can be seen that most populations produce a moderate or higher correlation between two perpendicular tests, when using the limited population set the correlations are markedly improved, Figure xxx shows the density curves for each population set. While the correlations between perpendicular splitting tests are fairly high, Figure xxx shows even with the high correlations within the limited population set, there can still be significant standard deviations of the differences between the two tests, implying a high error when attempting to identify individuals as superior. If instead the comparison is made between splitting test results and the true surface strain mean, again Figure xxx shows the destiny comparisons between  the full and limited population sets. Most striking here is the substantial movement toward the higher end of strain correlations of both population sets.  This can also be seen in Figure xxx where the standard deviation of the difference distribution appropriately half for all populations, along with the correlation between splitting test and true surface strain correlations approximately doubling. The implication ----