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"A helpful, user friendly introduction for quantitative data analysis using SPSS designed for students in both psychology and sociology fields." - Andrada Ivanescu, East Carolina University, US, in The American Statistician"Alan Bryman and Duncan Cramer take the reader on a journey through their first steps in using SPSS and data entry, through to how to decide which statistical technique is the most appropriate for their research and how to interpret each aspect of their analyses. This book is one of the most comprehensive and accessible books available on the market." - Professor Dominic Upton, Head of Psychology, University of Worcester, UK"Bryman and Cramer’s Quantitative Data Analysis has long been one of the best texts in the field. Crucially, it explains why something is done, as well as how. Most importantly, it does it without recourse to daunting formulae and calculations. It takes students from the beginnings of data analysis, assuming no knowledge of either statistics or SPSS, and by the end of it a student can be an accomplished analyst." - Malcolm Williams, Director, Cardiff University. School of Social Sciences, UK Alan Bryman is Professor of Organisational and Social Research at the School of Management, University of Leicester. His research interests include research methodology, leadership and organizational analysis. Duncan Cramer is Professor of Psychological Health in the Department of Social Sciences at Loughborough University. His research interests include mental health, personality, personal relationships, psychotherapy and counselling. Klappentext The authors provide a non-technical approach to quantitative data analysis and a user-friendly introduction to SPSS Statistics Version 19 for Windows. Zusammenfassung The authors provide a non-technical approach to quantitative data analysis and a user-friendly introduction to SPSS Statistics Version 19 for Windows. Inhaltsverzeichnis Preface. 1. Data Analysis and the Research Process. 2. Analyzing Data with Computers: First Steps with SPSS 19, 18 and 17. 3. Analyzing Data with Computers: Further Steps with SPSS 19, 18 and 17. 4. Concepts and Their Measurement. 5. Summarizing Data. 6. Sampling and Statistical Significance. 7. Bivariate Analysis: Exploring Differences between Scores on Two Variables. 8. Bivariate Analysis: Exploring Relationships. 9. Multivariate Analysis: Exploring Differences among Three or More Variables. 10. Multivariate Analysis: Exploring Relationships among Three or More Variables. 11. Aggregating Variables: Exploratory Factor Analysis. Answers to Exercises. Glossary. Bibliography. Index. ...
