1 option
Data analysis with SPSS for survey-based research / Saiyidi Mat Roni, Hadrian Geri Djajadikerta.
Springer Nature - Springer Mathematics and Statistics eBooks 2021 English International Available online
View online- Format:
- Book
- Author/Creator:
- Roni, Saiyidi Mat, author.
- Djajadikerta, Hadrian Geri, author.
- Language:
- English
- Subjects (All):
- SPSS for Windows.
- Social sciences--Statistical methods--Computer programs.
- Social sciences.
- Physical Description:
- 1 online resource (273 pages) : illustrations
- Place of Publication:
- Singapore : Springer, [2021]
- Summary:
- This book is written for research students and early-career researchers to quickly and easily learn how to analyse data using SPSS. It follows commonly used logical steps in data analysis design for research. The book features SPSS screenshots to assist rapid acquisition of the techniques required to process their research data. Rather than using a conventional writing style to discuss fundamentals of statistics, this book focuses directly on the technical aspects of using SPSS to analyse data. This approach allows researchers and research students to spend more time on interpretations and discussions of SPSS outputs, rather than on the mundane task of actually processing their data.
- Contents:
- Intro
- Preface
- Acknowledgement
- Preliminary Data Analysis Checklist
- Contents
- About the Authors
- Chapter 1: Research Instrument Design and Sample
- 1.1 Survey
- 1.1.1 Working with Directly Observed Variables
- 1.1.2 Designing Questions for Latent Variables
- 1.2 Sample Size
- References
- Chapter 2: SPSS Basics
- 2.1 Data and Variable Views
- 2.2 Output Window
- 2.3 SPSS Syntax
- Chapter 3: Preliminary Data Analysis: An Analysis Before the Analysis
- 3.1 Cleaning up Your Data: Monotone
- 3.2 Polishing Your Data: Missing Values and Outliers
- 3.2.1 Identifying and Recoding Missing Values
- 3.3 Missing Values Analysis (MVA)
- 3.3.1 Multiple Imputation (MI)
- 3.3.2 Expected Maximisation (EM)
- 3.3.3 Identifying and Treating Outliers
- 3.4 Normal Distribution
- 3.5 Data Transformation
- Chapter 4: Factor Analysis: Combining Related Question-Items into Latent Variables
- Chapter 5: Assess the Quality of Your Instrument
- 5.1 Reliability
- 5.2 Validity
- Chapter 6: Latent Variable
- 6.1 Addressing Biases
- 6.1.1 Non-Response Bias
- 6.1.2 Common Method Bias
- Chapter 7: Test of Differences Among Groups
- 7.1 t-Test: Testing Differences Between Two Groups
- 7.1.1 Independent Samples t-Test
- 7.1.2 Paired Samples t-Test
- 7.2 ANOVA: Testing More than Two Groups
- 7.3 ANCOVA: Testing Differences and Controlling for Covariate
- Chapter 8: Test of Correlations
- 8.1 Pearson Correlation
- 8.2 Pearson Correlation with Bootstrap
- Chapter 9: Regression
- 9.1 Simple Regression
- 9.1.1 Regression with Bootstrap
- 9.1.2 Quantile Regression
- 9.2 Multiple Regression
- 9.3 Hierarchical Multiple Regression
- Chapter 10: Non-Parametric Tests
- 10.1 Mann-Whitney U
- 10.2 Kruskal-Wallis
- 10.3 Jonckheere-Terpstra.
- 10.4 Chi-Square
- 10.5 Wilcoxon´s Sign Rank
- 10.6 Spearman Rho and Kendall Tau Correlation
- Bibliography
- Index.
- Notes:
- Includes bibliographical references and index.
- Description based on print version record.
- Other Format:
- 9789811601927
- ISBN:
- 981-16-0193-3
- OCLC:
- 1258659961
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.