Nonparametric Hypothesis Tests

Abstract

The parametric methods of the previous chapter required data measured at the interval or ratio levels and which is normally distributed. Business data are not always at these levels of measurement. Market research regularly produces data at the nominal (e.g. “agree” versus “disagree” with a proposition about a product) and ordinal (e.g. ranked preferences) levels. The study of consumer preference is a field in which data at nominal and ordinal levels are particularly evident. In such instances the analyst has recourse to nonparametric statistical methods. Serious doubts about the normality assumption even when the data are at the interval or ratio levels is another situation in which nonparametric methods may be preferred over parametric ones. Many authors refer to nonparametric methods as distribution free, in that they make relatively few assumptions about the nature of the population distribution.