Training Course in Data Analysis & Manipulation Using SPSS

Course Outline

Module I: Introduction to SPSS

• Overview of SPSS and its key applications
• Navigating the SPSS interface (Data View, Variable View, Syntax Editor)
• Importing and exporting data (Excel, CSV, text formats)
• Basic file management and SPSS workflow

Module II: Data Management & Manipulation

• Entering and organizing data in SPSS
• Defining, labeling, and managing variables
• Handling missing values and identifying outliers
• Merging, splitting, sorting files, and selecting cases
• Complex data reshaping and aggregation
• Using SPSS syntax for efficient data manipulation

Module III: Descriptive Statistics & Data Exploration

• Generating frequency tables and summary statistics
• Measures of central tendency and variability (mean, median, mode, SD, etc.)
• Cross-tabulations for categorical data examination
• Visual binning and exploring associations between variables

Module IV: Data Transformation & Computation

• Recoding variables and creating new computed fields
• Applying transformation commands via syntax
• Merging and splitting datasets
• Cleaning and preparing data through transformations

Module V: Data Visualization in SPSS

• Creating charts: histograms, bar charts, scatter plots, boxplots, etc.
• Customizing visuals for presentation clarity
• Best practices for visual data representation

Module VI: Inferential Statistics & Hypothesis Testing

• Conducting t-tests (one-sample, independent, paired)
• Analysis of variance (ANOVA) and post-hoc analysis
• Correlation measures: Pearson’s, Spearman’s, Kendall’s
• Running regression: simple and multiple linear regression
• Applying non-parametric tests such as chi-square, Mann-Whitney U, Kruskal–Wallis

Module VII: Advanced Modeling & Multivariate Analysis

• Logistic and ordinal regression techniques
• Performing factor analysis and principal component analysis (PCA)
• Cluster analysis: k-means and hierarchical clustering
• Conducting reliability tests (e.g., Cronbach’s Alpha)

Module VIII: SPSS Syntax, Automation & Reporting

• Writing and executing SPSS syntax for reproducibility
• Automating repetitive analyses with syntax and macros
• Exporting, customizing, and managing output for reporting
• Tailoring reports for different audiences (executives, technical reports, etc.)

Module IX: Survey & Longitudinal Data Analysis

• Handling and analyzing survey data (Likert scales, frequency, and cross-tabs)
• Time-series or longitudinal data techniques
• Advanced survey techniques: weighting, complex samples, and case studies

Module X: Final Project & Application

• Applying all tools to a comprehensive dataset
• Cleaning, analyzing, visualizing, and modeling data
• Presenting findings through polished outputs and dashboards