• Summary
  • Contents
  • Subject index

A must-have reference resource for qualitative management researchers, this dictionary contains over 90 entries covering the fundamentals of qualitative methodologies; covering both analysis and implementation. Each entry gives an introduction to the topic, lists the key relevant features, gives a worked example, a concise summary and a selection of further reading suggestions. It is suitable for researchers and academics who need a handy and quick point of reference.

Data Transformation
Data transformation
Introduction

Data transformations are techniques that transform raw data collected to yield data and images more easily understood. Data transformations are a remedy for failures of normality.

Key Features

It is important to meet the assumption of normality, since statistical inference or exploratory power is weakened when departures occur from normality (Cohen et al., 2003; Hutcheson and Sofroniou, 1999). The most straightforward implication that arises as a consequence of the typical skewed distribution of variable ratings is technical in nature and relates to both the analysis and the interpretation of data. Given a skewed distribution, of any variable, the arithmetical mean is no longer an appropriate measure of central tendency since it excludes considerable information about the variable. Indeed, in this instance, ‘average score’ is a ...

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