Data Analysis For Social Workers

This introductory text clearly presents information on the analysis and interpretation of data generated by social workers in practice. It covers the nature of data, measures of variability, crosstabulation analysis, correlational methods, hypothesis testing, and multiple regression. Pertinent social work examples are used throughout.

This user-friendly text is designed specifically for social work students who are intimidated by the prospect of taking a Statistics course. With its engaging, conversational writing style and numerous examples and problems, social work students will quickly learn to understand and interpret both quantitative and qualitative data. The text's flexibility makes it suitable for a variety of teaching styles. Instructors who want their students to get the actual "feel" of computing a chi square can use the "Formula Alerts" to calculate certain statistics manually; other instructors may want students to use the step-by-step computer applications to produce the same results.

"This chapter is an introduction to applied cross-cultural data analysis, and addressed the concepts of culture and how culture can be integrated into social work research. We review the definition of culture and how it has been understood and examined in research across different disciplines. We present an overview of the theories and frameworks of cross-cultural analysis, and provide the lens through which culture is examined through the techniques and approaches that are used in this book"--

Using real social work examples written specifically to ally student fears Research and Statistics for Social Workers brings research and statistics together bridging the gap to practice. This book covers - conceptualization, ethics, cultural competence, design, qualitative research, individual and program evaluation as well as nonparametric and parametric statistical tests. The tests are explained narratively, mathematically as well as with a comprehensive step-by-step, fully illustrated SPSS computer analysis of social work data.

This slim volume is one of a number of excellent guides published as part of Oxford's "Pocket Guide to Social Work Research Methods" series. Compact but comprehensive, it provides a thorough introduction to one of the fastest-growing genres of research in the social work field today: secondary data analysis. After an all-too-brief summary of what constitutes this genre and a balanced analysis of its advantages and disadvantages, Vartanian (Bryn Mawr) provides guidelines for those considering the feasibility and appropriateness of using secondary data in their work. He then offers extensive summaries of 29 of the most commonly used secondary data sets. For all of the data sets, he provides a full and complete description, including key characteristics and where and how to access them. He also provides, most valuably, citations to examples of how researchers have recently used them in their empirical work. Rather redundantly, a similar package of information appears in appendixes at the end of the book. This is an admirable contribution whose only detractions are the rather random and poorly identified screenshots and other "pictures" interspersed throughout the text. Those seriously considering using secondary data analysis in their research should find this book immensely beneficial. Summing Up: Highly recommended. Graduate students and faculty/researchers. Graduate Students; Researchers/Faculty. Reviewed by J. C. Altman.

Representing some of the best research efforts currently found among social workers, Quantitative Methods in Social Work serves as both a guide and a challenge to social work researchers interested in the application of quantitative methods to social work problem solving. This application of research methods has not been described or discussed adequately in any formal way until now. In a comprehensive manner, this book documents the most advanced quantitative methodologies currently applied by social work researchers and describes issues and techniques that accompany specific applications. It increases social workers'understanding of state-of-the-art applied statistical analysis, enabling them to become more competent and competitive in research and the teaching of research strategies. Quantitative Methods in Social Work addresses three types of methodological issues: measurement, the incorporation of nonquantitative variables in quantitative data analysis, and the use of quantitative analytic techniques to model and assess complex social phenomena. Chapters cover the use of computers for content analysis, structural equation modeling in measurement, logistic regression, loglinear analysis, event history analysis, social network analysis, and discussions of moderator variables and interaction effects in multiple regression. Social work faculty and doctoral students, along with other human service professionals who want to increase their understanding of applied statistical analysis in social and behavioral research, will find the information they need in this informative book.

CD-ROM for Windows has an easy-to-use interface.