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This essential guide for education students and researchers explains how to use quantitative methods for analysing educational data using IBM SPSS Statistics. By using datasets from real-life educational research, it demonstrates key statistical techniques that you will need to know, explaining how each procedure can by run on IBM SPSS Statistics. Datasets discussed in the book are downloadable, allowing you to hone your skills as you read. In this third edition, explanations have been updated with figures and screenshots from SPSS version 28, alongside a range of new research examples…mehr
This essential guide for education students and researchers explains how to use quantitative methods for analysing educational data using IBM SPSS Statistics.
By using datasets from real-life educational research, it demonstrates key statistical techniques that you will need to know, explaining how each procedure can by run on IBM SPSS Statistics. Datasets discussed in the book are downloadable, allowing you to hone your skills as you read.
In this third edition, explanations have been updated with figures and screenshots from SPSS version 28, alongside a range of new research examples and updated further reading.
Daniel Muijs is Dean of the Faculty of Education and Society at Academica University of Applied Sciences in Amsterdam.
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Autorenporträt
Daniel Muijs is Dean of the Faculty of Education and Society at Academica University of Applied Sciences in Amsterdam, and visiting professor at the University of Southampton. He has worked in education departments at a range of UK universities, as well as at Ofsted, the English inspectorate of schools and social care. He is an experienced quantitative researcher and has taught quantitative methods to students from undergraduate to PhD levels.
Inhaltsangabe
Chapter 1. Introduction to quantitative research Chapter 2. Experimental and quasi-experimental research Chapter 3. Designing non-experimental studies Chapter 4. Validity, reliability and generalisability Chapter 5. Introduction to IBM SPSS Statistics and the data set Chapter 6. Univariate statistics Chapter 7. Bivariate analysis: comparing two groups Chapter 8. Bivariate analysis: looking at the relationship between two variables Chapter 9. Multivariate analysis: using regression models to look at the relationship between several predictors and one dependent variable Chapter 10. Using analysis of variance to compare more than two groups Chapter 11. Developing scales and measures: item and factor analysis Chapter 12. One step beyond: introduction to multilevel modelling and structural
Chapter 1. Introduction to quantitative research Chapter 2. Experimental and quasi-experimental research Chapter 3. Designing non-experimental studies Chapter 4. Validity, reliability and generalisability Chapter 5. Introduction to IBM SPSS Statistics and the data set Chapter 6. Univariate statistics Chapter 7. Bivariate analysis: comparing two groups Chapter 8. Bivariate analysis: looking at the relationship between two variables Chapter 9. Multivariate analysis: using regression models to look at the relationship between several predictors and one dependent variable Chapter 10. Using analysis of variance to compare more than two groups Chapter 11. Developing scales and measures: item and factor analysis Chapter 12. One step beyond: introduction to multilevel modelling and structural
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