Application of the Non-Parametric Signals Test to a Company

Abstract

Objective: The aim of this paper is to show the application of the Non-Parametric Sign Test in problems involving the testing of central tendency values. Theoretical framework: Non-parametric methods are widely used in the study of populations that are taken in rank order (such as a movie that receives one to four star ratings). The use of non-parametric methods may also be necessary when the data has a ranking but no clear numerical interpretation, such as when accessing preferences. In terms of scale, non-parametric methods result in data that is "in order" (Thatcher et al., 2005) Method: Data was taken from a company in the South of Rio de Janeiro and a case study was carried out using the Non-Parametric Sign Test. Final Considerations: Initially it proved unfeasible to use a Parametric Test because the Anderson-Darling Test showed that the Assumption of Normality was not confirmed and finally the Non-Parametric Sign Test showed that the hypothetical Median really is the correct measure of Central Tendency. Implications of the research: The use of Non-Parametric Tests is widespread in scientific literature and has proven to be highly effective in dealing with data where the assumptions of Normality are not confirmed. Originality/value: Despite being well-known statistical tools, Non-Parametric Tests are widely used and can bring innovations to their application, as in the case of the company in question.