Flora: Statistical Methods for the Social and Behavioural Sciences
Statistical Methods for the Social and Behavioural Sciences is the essential guide for those looking to extend their understanding of the principles of statistics, and begin using the right statistical modeling method for their own data. It is particularly suited to second or advanced courses in statistical methods across the social and behavioural sciences.
Learn by applying, with input and output files for R, SAS, SPSS, and Mplus. Click below to download datasets and files for each chapter.
- Chapter 1: Foundations of Statistical Modeling Demonstrated with Simple Regression
- Chapter 2: Multiple Regression with Continuous Predictors
- Chapter 3: Regression with Categorical Predictors
- Chapter 4: Interactions in Multiple Regression: Models for Moderation
- Chapter 5: Using Multiple Regression to Model Mediation and Other Indirect Effects
- Chapter 6: Introduction to Multilevel Modeling
- Chapter 7: Basic Matrix Algebra for Statistical Modeling
- Chapter 8: Exploratory Factor Analysis
- Chapter 9: Structural Equation Modeling I: Path Analysis
- Chapter 10: Structural Equation Modeling II: Latent Variable Models
- Chapter 11: Growth Curve Modeling
- Additional Datasets