Course Outline

Module 1: Introduction to Advanced SPSS Features

• Overview of SPSS capabilities
• Advanced data manipulation tools
• Customizing SPSS environment for efficiency

Module 2: Data Preparation and Cleaning

• Techniques for handling missing data
• Data transformation methods
• Outlier detection and treatment

Module 3: Advanced Data Manipulation

• Creating and managing variables
• Complex data reshaping and aggregation
• Merging and appending datasets

Module 4: Statistical Analysis Techniques

• Advanced descriptive statistics
• Inferential statistics: t-tests, ANOVA, and MANOVA
• Non-parametric tests and their applications

Module 5: Regression Analysis and Modeling

• Multiple regression analysis
• Logistic regression and binary outcomes
• Model diagnostics and validation

Module 6: Factor Analysis and Dimension Reduction

• Principal Component Analysis (PCA)
• Exploratory Factor Analysis (EFA)
• Interpreting factor loadings and results

Module 7: Advanced Data Visualization

• Creating and customizing advanced charts and graphs
• Interactive visualizations in SPSS
• Best practices for data presentation

Module 8: Time Series Analysis

• Techniques for analyzing time series data
• Seasonal decomposition and forecasting
• Handling trends and patterns in time series

Module 9: Advanced Statistical Techniques

• Cluster analysis and segmentation
• Survival analysis and event history analysis
• Structural Equation Modeling (SEM)

Module 10: Reporting and Interpretation of Results

• Generating comprehensive reports in SPSS
• Communicating findings effectively
• Case studies and practical applications