- 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.
Factor analysis attempts to identify the underlying structure in a data set by defining a small number of factors that capture the variation in the collected data. Factor analysis assumes that relationships between variables are due to the effects of underlying factors and that observed correlations are the result of variables sharing common causes. Describing a data set in terms of factors (or latent variables as they are sometimes called) is often useful at a theoretical level as it may identify the underlying processes which determined the correlations among the variables. This often allows a simpler and clearer interpretation of the relationships in the data. Factor analysis is also useful at a more practical level as it reduces the number of variables ...