Reviews

Analyzing Soical Science Data

The primary focus of this book is the analysis of quantitative research data. As such, its title is a little misleading as its emphasis is quantitative analysis as opposed to both quantitative and qualitative data analysis. However, the book is clearly written and gives the underpinning rationale for statistical analysis – something which is frequently omitted in similar texts.

The text is structured around 50 key problems often encountered by quantitative social science researchers. In adopting this stance, de Vaus reduces the complexity of statistical analysis into bite-size chunks. For example, the problem-solving approach enables the reader to focus on particular areas of concern. Many helpful examples of social-science data sets are given to illustrate points made in the text, and the reader is given a step-by-step guide on how to deal with data analysis. Additionally, the data sets used, while not totally nursing-focused, can be related to by many nurse researchers.

Generally, de Vaus takes the reader through the intricacies of preparing data for analysis, preparing variables for analysis, reducing the amount of data to analyse, analysing a single variable and multivariate analysis.

A criticism could be made that, on occasions, the author ventures into design rather than analysis issues. For example, how to

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The text is structured around 50 key problems often encountered by quantitative social science researchers. In adopting this stance, de Vaus reduces the complexity of statistical analysis into bite-size chunks. For example, the problem-solving approach enables the reader to focus on particular areas of concern. Many helpful examples of social-science data sets are given to illustrate points made in the text, and the reader is given a step-by-step guide on how to deal with data analysis. Additionally, the data sets used, while not totally nursing-focused, can be related to by many nurse researchers.

Generally, de Vaus takes the reader through the intricacies of preparing data for analysis, preparing variables for analysis, reducing the amount of data to analyse, analysing a single variable and multivariate analysis.

A criticism could be made that, on occasions, the author ventures into design rather than analysis issues. For example, how to build a good Likert scale is an inclusion – this is slightly at odds with other content of the book. However, these diversions enhance the general broad appeal of this publication.

In summary, de Vaus’s book will be of potential interest to the uninitiated quantitative researcher. It provides a good introduction to quantitative data analysis.

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