Doing Quantitative Research in Education with SPSS

This accessible and authoritative introduction is essential for education students and researchers needing to use quantitative methods for the first time.

Using datasets from real-life educational research and avoiding the use of mathematical formulae, the author guides students through the essential techniques that they will need to know, explaining each procedure using the latest version of SPSS. The datasets can also be downloaded from the book's website, enabling students to practice the techniques for themselves.

This revised and updated second edition now also includes more advanced methods such as log linear analysis, logistic regression, and canonical correlation.

Written specifically for those with no prior experience of quantitative research, this book is ideal for education students and researchers in this field.

Auteur

Professor Daniel Muijs is Chair of Education. Previously he worked at the University of Manchester as Chair of Pedagogy and Teacher Development at the University of Manchester, School of Education, as Chair of School Leadership and Management at the University of Newcastle and as senior at Warwick Institute of Education. He is an acknowledged expert in the field of Educational and Teacher Effectiveness and is co-editor of the journal 'School Effectiveness and School Improvement'. He has published widely in the areas of educational effectiveness, leadership and research methods, and has conducted research for government agencies (DCSF, NCSL, QCA), Charitable Trusts (Gatsby) and Research Councils (ESRC).

Contenu

Introduction to Quantitative Research
Experimental and Quasi-Experimental Research
Designing Non-Experimental Studies
Validity, Reliability and Generalizability
Introduction to PASW Statistics (IBM SPSS) and the Data Set
Univariate Statistics
Bivariate Analysis: Comparing Two Groups
Bivariate Analysis: Looking at the Relationship between Two Variables
Multivariate Analysis: Using Regression Models to Look at the Relationship between Several Predictors and One Dependent Variable
Using Analysis of Variance to Compare More Than Two Groups
Developing Scales and Measures: Item and Factor Analysis
One Step beyond: Introduction to Multilevel Modeling and Structural Equation Modeling