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Course Outline
Getting Started with SPSS
- Overview of the SPSS interface and functionality for government use.
- Navigating dialog boxes, the Data Editor, and Variable View.
- Importing, exporting, and managing datasets for government analysis.
Data Preparation and Management
- Understanding variables and measurement scales in governmental contexts.
- Data entry, cleaning, and transformation techniques for government datasets.
- Creating and managing databases in SPSS for government use.
Working with Syntax and Automation
- Introduction to SPSS command syntax for efficient data processing.
- Automating analyses with syntax scripts for government operations.
- Integrating SPSS with Python and R for enhanced analytical capabilities in government applications.
Descriptive Statistics and Visualization
- Measures of central tendency and dispersion for government datasets.
- Standardization and z-scores in governmental data analysis.
- Creating tables, charts, and interactive visualizations for government reporting.
Inferential Statistics
- Hypothesis testing and statistical significance in governmental research.
- Correlation and regression analysis for government studies.
- t-tests, ANOVA, and chi-square tests in governmental analyses.
Predictive Modeling with SPSS
- Linear and logistic regression models for government forecasting.
- Decision trees and classification models in governmental applications.
- Time series forecasting and survival analysis for government planning.
Advanced Techniques and Applications
- Factor analysis and cluster analysis in governmental research.
- Handling missing values and outliers in government datasets.
- Case studies in marketing, health, and social sciences for government insights.
Reporting and Sharing Results
- Formatting and customizing SPSS outputs for governmental reports.
- Exporting results to Word, Excel, and PDF for government documentation.
- Creating professional reports for informed decision-making in government operations.
Summary and Next Steps
Requirements
- Basic knowledge of statistical and data analysis principles (e.g., variables, hypotheses, significance)
- Proficiency with Microsoft Excel or comparable spreadsheet applications
- Prior experience with research methodologies or dataset management is advantageous but not mandatory
Audience
- Data Analysts
- Research Professionals
- Scientific Investigators
- Any individuals seeking to develop practical skills in SPSS and predictive analytics for government and other public sector roles
14 Hours
Testimonials (3)
basics and loved the prepared documents and exercises
Rekha Nallam - GE Medical Systems Polska Sp. z o.o.
Course - Introduction to Predictive AI
The variation with exercise and showing.
Ida Sjoberg - Swedish National Debt Office
Course - Econometrics: Eviews and Risk Simulator
Very practical
