The second edition of Interpreting Quantitative Data with IBM SPSS Statistics is an invaluable resource for students analysing quantitative data for the first time. The book clearly sets out a range of statistical techniques and their common applications, explaining their logic and links to the research process. It also shows how SPSS can be used as a tool to aid analysis. Key features of the second edition include: - new chapters on one-way and two-way ANOVA, the Chi-square test and linear regression. - SPSS lab sessions following each chapter which demonstrate how SPSS can be used in practice - sets of exercises and 'real-life' examples to aid teaching and learning - lists of key terms to aid revision and further reading to enhance students' understanding - an improved text design making the book easier to navigate - a companion website with answers to the labs and exercises, along with additional data sets and powerpoint slides
In this fully updated and expanded second edition, Carol Grbich provides a guide through current issues in the analysis of qualitative data. Packed with detailed examples, a glossary, further reading lists and a section on writing up, this book is exactly what you need to get you started in qualitative research. The new edition covers analytical approaches including: - grounded theory - classical, existential and hermeneutic phenomenology - feminist research including memory work - classical, auto- and cyberethnography as well as ethnodrama - content, narrative, conversation and discourse analysis - visual interpretation - semiotic, structural and poststructural analyses A one-stop-shop for students new to qualitative data analysis!
Peter Vik's Regression, ANOVA, and the General Linear Model: A Statistics Primer demonstrates basic statistical concepts from two different perspectives, giving the reader a conceptual understanding of how to interpret statistics and their use. The two perspectives are (1) a traditional focus on the t-test, correlation, and ANOVA, and (2) a model-comparison approach using General Linear Models (GLM). This book juxtaposes the two approaches by presenting a traditional approach in one chapter, followed by the same analysis demonstrated using GLM. By so doing, students will acquire a theoretical and conceptual appreciation for data analysis as well as an applied practical understanding as to how these two approaches are alike.
As Derek Jeter strolls toward the plate, the announcer tosses out a smattering of statisticsfrom hitting streaks to batting averages. But what do the numbers mean? And how can Americas favorite pastime be a model for learning about statistics? Sandlot Stats is an innovative textbook that explains the mathematical underpinnings of baseball so that ......
It is no exaggeration to say that virtually all quantitative research in the social sciences is done with correlation and regression analysis (CRA) and their siblings and offspring. CRA are fundamental analytic tools in fields like sociology, economics and political science as well as applied disciplines such as marketing, nursing, education and social work. The subject is of great substantive importance; therefore, distinguished editors, W. Paul Vogt and R. Burke Johnson, have ordered the growing research literature on the use of CRA according to its natural steps. Each step in this logical progression constitutes a volume in this collection: Volume One: Regression and Its Correlational Foundations and Concomitants Volume Two: Factor Analysis, Regression Diagnostics, and Model Building Volume Three: Data Transformations, Curvilinear Regression, and Logistic Regression Volume Four: Multi-Level Regression Modeling, Structural Equation Modeling and Mixed Regression
The second edition of Interpreting Quantitative Data with IBM SPSS Statistics is an invaluable resource for students analysing quantitative data for the first time. The book clearly sets out a range of statistical techniques and their common applications, explaining their logic and links to the research process. It also shows how SPSS can be used as a tool to aid analysis. Key features of the second edition include: - new chapters on one-way and two-way ANOVA, the Chi-square test and linear regression. - SPSS lab sessions following each chapter which demonstrate how SPSS can be used in practice - sets of exercises and 'real-life' examples to aid teaching and learning - lists of key terms to aid revision and further reading to enhance students' understanding - an improved text design making the book easier to navigate - a companion website with answers to the labs and exercises, along with additional data sets and powerpoint slides
This comprehensive Second Edition offers readers a complete guide to carrying out research projects involving structural equation modeling (SEM). Updated to include extensive analysis of AMOS' graphical interface, a new chapter on latent curve models and detailed explanations of the structural equation modeling process, this second edition is the ideal guide for those new to the field. The book includes: Learning objectives, key concepts and questions for further discussion in each chapter. Helpful diagrams and screenshots to expand on concepts covered in the texts. Real life examples from a variety of disciplines to show how SEM is applied in real research contexts. Exercises for each chapter on an accompanying companion website. A new glossary. Assuming no previous experience of the subject, and a minimum of mathematical knowledge, this is the ideal guide for those new to SEM and an invaluable companion for students taking introductory SEM courses in any discipline. Niels J. Blunch was formerly in the Department of Marketing and Statistics at the University of Aarhus, Denmark
This comprehensive Second Edition offers readers a complete guide to carrying out research projects involving structural equation modeling (SEM). Updated to include extensive analysis of AMOS' graphical interface, a new chapter on latent curve models and detailed explanations of the structural equation modeling process, this second edition is the ideal guide for those new to the field. The book includes: Learning objectives, key concepts and questions for further discussion in each chapter. Helpful diagrams and screenshots to expand on concepts covered in the texts. Real life examples from a variety of disciplines to show how SEM is applied in real research contexts. Exercises for each chapter on an accompanying companion website. A new glossary. Assuming no previous experience of the subject, and a minimum of mathematical knowledge, this is the ideal guide for those new to SEM and an invaluable companion for students taking introductory SEM courses in any discipline. Niels J. Blunch was formerly in the Department of Marketing and Statistics at the University of Aarhus, Denmark
Discussing the issues that surround a range of statistical questions and controversies, the Second Edition reveals divergent perspectives on these issues and offers practical advice and examples for conducting statistical analyses that reflect the authors' interpretation of the consensual wisdom of the field. It is a compendium of statistical knowledge - some theoretical, some applied - that addresses those questions most frequently asked by students and colleagues struggling with statistical analyses.
