Buch, Englisch, 468 Seiten, Format (B × H): 184 mm x 241 mm, Gewicht: 830 g
Buch, Englisch, 468 Seiten, Format (B × H): 184 mm x 241 mm, Gewicht: 830 g
ISBN: 978-93-5388-328-7
Verlag: SAGE Publications
A concise introduction to data analysis for beginners and intermediate students using IBM – Statistical Package for Social Sciences (SPSS)
The present book elaborates on the basic understanding and application of statistical tests and data analysis using hypothetical datasets and SPSS version 22.0. It enhances self-learning and develops thorough understanding of the concepts through step-by-step processes for quick comprehension, and screen images, dialog boxes and exhibits for better interaction with the software.
Spanning across 17 chapters, Data Analysis Using SPSS begins from the stages of data entry and goes on till editing and data visualization. It takes the readers through descriptive statistics, frequency, univariate, bivariate and regression analysis, cross-tabulation, linear models, and non-parametric test procedures. This textbook will act as a helpful companion to students of management, humanities and social sciences, agriculture and life sciences, as well as young research scholars.
Key Features:
• Main and sub-dialog boxes of SPSS containing commands of specific test techniques incorporated in the text for effective interaction with the software
• Exercises and practice questions to enhance analytical understanding
• Addition chapters on Means Analysis, One-way ANOVA, and Probability and Sampling Distribution provided as web supplement for advance reading
Autoren/Hrsg.
Weitere Infos & Material
Preface
Acknowledgements
Part I: Basics of SPSS Windows
Orientation to SPSS Windows
Creating and Editing Data
PART II: Data Visualization and Descriptive Statistics
Displaying Data with Charts and Graphs
Frequency Analysis and Descriptive Statistics
Exploratory Data Analysis
PART III: Cross-Tabulation
Data Analysis with Cross-Tabulation
PART IV: Univariate Statistical Inferences
Independent Sample t-Test
Paired Sample t-test
One-Sample t-test
PART V: Experimental Designs: Analysis of Variance
One-Way Analysis of Variance (ANOVA)
Two-Way ANOVA Factorial Design
PART VI: Relationship Measurement and Predictive Analysis
Measures of Association
Simple Linear Regression Analysis
Multiple Linear Regression Analysis
Binary Logistics Regression
PART VII: Non-Parametric Tests
Non-Parametric Tests
PART VIII: Reliability and Probability Distribution
Reliability Analysis
Means Analysis
One-Way ANOVA Repeated Measures
Probability and Sampling Distribution
Appendix
Index




