??Non-parametric methods are widely used for studying populations that take on a ranked order
(such as movie reviews receiving one to four stars). The use of non-parametric methods may be
necessary when data have a ranking but no clear numerical interpretation such as when
assessing preferences. In terms of levels of measurement non-parametric methods result in
ordinal data. As non-parametric methods make fewer assumptions their applicability is much
wider than the corresponding parametric methods. In particular they may be applied in
situations where less is known about the application in question. Also due to the reliance on
fewer assumptions non-parametric methods are more robust. Non-parametric methods have many
popular applications and are widely used in research in the fields of the behavioral sciences
and biomedicine. This is a textbook on non-parametric statistics for applied research. The
authors propose to use a realistic yet mostly fictional situation and series of dialogues to
illustrate in detail the statistical processes required to complete data analysis. This book
draws on a readers existing elementary knowledge of statistical analyses to broaden his her
research capabilities. The material within the book is covered in such a way that someone with
a very limited knowledge of statistics would be able to read and understand the concepts
detailed in the text. The real world scenario to be presented involves a multidisciplinary team
of behavioral medical crime analysis and policy analysis professionals work together to
answer specific empirical questions regarding real-world applied problems. The reader is
introduced to the team and the data set and through the course of the text follows the team as
they progress through the decision making process of narrowing the data and the research
questions to answer the applied problem. In this way abstract statistical concepts are
translated into concrete and specific language. This text uses one data set from which all
examples are taken. This is radically different from other statistics books which provide a
varied array of examples and data sets. Using only one data set facilitates reader-directed
teaching and learning by providing multiple research questions which are integrated rather than
using disparate examples and completely unrelated research questions and data.
