Simulations were performed to study the eifects of violations of the normality assumption on the / test of the Pearson product-moment correlation coefficient. It was found that as long as the variables were independent, the test was robust to violations of normality, even extreme violations in combined distributions. However, large effects for violations of normality were found when the variables were not independent, even though the population correlation was zero.

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Using a probabilistic category learning paradigm, 6 experiments explored irrelevant information and 4 current models. Utilization of relevant configural information was lowered by the presence of an irrelevant dimension, both if that was the only relevant information and if a dimension was also relevant. An irrelevant cue value lowered the utilization of relevant cue values. An additional relevant dimension had a larger degrading effect on the utilization of a relevant dimension than an additional irrelevant dimension, thereby suggesting that the effect of irrelevant information is due to the complexity of the environment rather than to factors particular to the irrelevant nature of the information. The current models failed to fit the findings. However, results showing that memory errors account for salience effects provide a direction for revising one of the models.

Estimates of the sensitivity and specificity of these common tests for carpal tunnel syndrome support their widespread clinical use.