“The power of sensory discrimination methods” (PSDM) was published in this journal in 1993. PSDM clarified the need for power considerations in the interpretation of testing results while providing a series of sample size tables. Despite the fact that the data considered in PSDM were binomially distributed, a normal approximation was used that both overestimated power and underestimated sample sizes. Although exact power functions have been examined in the sensory literature, the unusual behavior of these functions has not been embraced; the fact that increasing sample size can decrease power has not yet been incorporated into stable sample size recommendations. In this paper, we provide sample size recommendations with the property that any larger sample sizes also have the desired level of power. These recommendations are given in the form of tables updating those found in PSDM. In addition, a relatively new discrimination testing method known as the tetrad test has grown in popularity recently and this test now needs to be examined from a power perspective. We show that the tetrad test is remarkably powerful for an unspecified test and in some cases only requires one third the sample size as that required by the triangle test. PRACTICAL APPLICATIONS This paper contains three main practical applications. First, we provide sample size recommendations, including tables, based on the exact power function as determined by the binomial distribution. In particular, this paper is the first to provide exact sample size recommendations such that all larger sample sizes continue to have the desired level of power. Next, we use the exact power analysis to recommend that only the 2‐alternative forced choice (AFC); instead of, for example, the 3‐AFC or the specified tetrad test be used for forced choice testing in which an attribute of interest is specified to distinguish the samples. Finally, we provide a power analysis of the unspecified tetrad test for the first time in the sensory literature and show that in some cases, the tetrad test only requires one third the sample size as the triangle test. This last point could lead to both significant resource savings and improved confidence for researchers throughout sensory science.

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