Courses
SPSS Course
This hands-on course teaches data visualization techniques using Python libraries for custom charts, Power BI for interactive dashboards, and Tableau for advanced storytelling with data. Students will learn to clean, analyze, and present insights from datasets, building skills for effective communication in business and analytics through practical projects and real-world applications.
About Course
Career Prospects
- Data Analyst
- Statistician
- Market Researcher
- Biostatistician
- Research Analyst
- Survey Analyst
- Quantitative Analyst
- Social Scientist
- Clinical Data Analyst
- Business Intelligence Analyst
Course Curriculum
Module 1: Introduction to SPSS
- SPSS Interface Navigation
- Data Editor Basics
- Variable View and Data View
- File Management
- Basic Commands
Module 2: Data Entry and Import
- Manual Data Entry
- Importing from Excel/CSV
- Data Types and Formats
- Handling Missing Values
- Data Validation
Module 3: Data Cleaning and Transformation
- Recoding Variables
- Computing New Variables
- Sorting and Filtering
- Merging Datasets
- Splitting Files
Module 4: Descriptive Statistics
- Frequencies and Crosstabs
- Measures of Central Tendency
- Dispersion Statistics
- Custom Tables
- Explore Command
Module 5: Data Visualization
- Chart Builder Basics
- Bar and Pie Charts
- Histograms and Boxplots
- Scatterplots
- Editing Graphs
Module 6: Hypothesis Testing
- T-Tests (One-Sample, Independent, Paired)
- Chi-Square Tests
- Non-Parametric Tests
- Confidence Intervals
- P-Values Interpretation
Module 7: Correlation and Regression
- Bivariate Correlation
- Simple Linear Regression
- Multiple Regression
- Logistic Regression
- Residual Analysis
Module 8: Advanced Analysis Techniques
- ANOVA (One-Way, Two-Way)
- Factor Analysis
- Cluster Analysis
- Discriminant Analysis
- Reliability Analysis
Module 9: Reporting and Output Management
- Output Viewer Navigation
- Exporting Results
- Syntax Editor Usage
- Automating Tasks
- Report Generation
Module 10: Projects and Applications
- Real-World Case Studies
- Capstone Project
- Data Interpretation
- Ethical Considerations
- Career Preparation
Skills and Tools Covered
- SPSS
- Chart Builder
- Syntax Editor
- Output Viewer
- Excel Integration
- CSV Importer
Duration
2 Weeks
Cost
KES. 10,000