Statistical tests

ABX test

An ABX test is a method of comparing two choices of sensory stimuli to identify detectable differences between them. A subject is presented with two known samples (sample A, the first reference, and sample B, the second reference) followed by one unknown sample X that is randomly selected from either A or B. The subject is then required to identify X as either A or B. If X cannot be identified reliably with a low p-value in a predetermined number of trials, then the null hypothesis cannot be rejected and it cannot be proven that there is a perceptible difference between A and B. ABX tests can easily be performed as double-blind trials, eliminating any possible unconscious influence from the researcher or the test supervisor. Because samples A and B are provided just prior to sample X, the difference does not have to be discerned from assumption based on long-term memory or past experience. Thus, the ABX test answers whether or not, under ideal circumstances, a perceptual difference can be found. ABX tests are commonly used in evaluations of digital audio data compression methods; sample A is typically an uncompressed sample, and sample B is a compressed version of A. Audible compression artifacts that indicate a shortcoming in the compression algorithm can be identified with subsequent testing. ABX tests can also be used to compare the different degrees of fidelity loss between two different audio formats at a given bitrate. ABX tests can be used to audition input, processing, and output components as well as cabling: virtually any audio product or prototype design. (Wikipedia).

ABX test
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Simpson's paradox | Confidence interval | P-value | Experiment | MUSHRA | Pooled variance | Statistical significance | Null hypothesis