Holdings Information

Bibliographic Record Display

• Title:[Doing quantitative research in education with SPSS]
  Doing quantitative research in education with IBM SPSS statistics / Daniel Muijs.
  
•    
• Author/Creator:Muijs, Daniel, author.
  
• Other Contributors/Collections:Muijs, Daniel. Doing quantitative research in education with SPSS. Second edition.
  
• Published/Created:Los Angeles : SAGE, 2022.
  

• Holdings

  Holdings Record Display

  • Location:EDUCATION LIBRARY stacksWhere is this?
    
  • Call Number: LB1028 .M775 2022
    
  • Number of Items:1
    
  • Status:Available
    

   
• Library of Congress Subjects:Education--Research--Methodology.
  Quantitative research.
  
• Subject(s):SPSS (Computer file)
  
• Edition:Third edition.
  
• Description:viii, 218 pages : illustrations ; 25 cm
  
• Summary:"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."-- Publisher's description.
  
• Notes:Previous edition: published as Doing quantitative research in education with SPSS. 2011.
  Includes bibliographical references and index.
  
• ISBN:9781526432674 (hbk.)
  1526432676 (hbk.)
  9781526432681 (pbk.)
  1526432684 (pbk.)
  9781526472786 (ePub ebook)
  9781526472779 (PDF ebook)
  
• Contents:Machine generated contents note: 1. Introduction to quantitative research
  2. Experimental and quasi-experimental research
  3. Designing non-experimental studies
  4. Validity, reliability and generalisability
  5. Introduction to IBM SPSS Statistics and the data set
  6. Univariate statistics
  7. Bivariate analysis: comparing two groups
  8. Bivariate analysis: looking at the relationship between two variables
  9. Multivariate analysis: using regression models to look at the relationship between several predictors and one dependent variable
  10. Using analysis of variance to compare more than two groups
  11. Developing scales and measures: item and factor analysis
  12. One step beyond: introduction to multilevel modelling and structural equation modelling.