JUSTIFYING COUNT‐BASED COMPARISONS

ABSTRACTCount‐based comparisons such as “7 out of 10” or “2 to 1” are often used to quantify superior product performance. Because of experimental variability, statistics are needed to ensure confidence in such comparisons. Even so, count‐based comparisons commonly appear without any statistical treatment of the data. In this article, we discuss statistics to support these comparisons. Specifically, we identify two different types of count‐based comparisons: count‐based proportional comparisons and count‐based ratio comparisons. We then provide statistics to justify these comparisons before providing significance tables for practitioners.PRACTICAL APPLICATIONSWhen an advertiser claims that one product offers a benefit over another, the consumer needs to be reasonably sure of experiencing the purported benefit. Similarly, when a product test result is compared with a benchmark, it is worth considering how confident we are in the comparison. Without statistics, there is no reason to expect that the results of a particular product test will be experienced in the future. Until now, the statistics needed to justify count‐based comparison such as “7 out of 10” and “2 to 1” have not appeared in the sensory literature. In this article, we remedy this lack by providing both statistical discussion and significance tables for practitioners.