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Course Outline
Introduction to SPSS
- Overview of the SPSS interface and core functionalities.
- Navigating dialog boxes, the data editor, and variable view.
- Importing, exporting, and managing datasets.
Data Preparation and Management
- Understanding variables and measurement scales.
- Data entry, cleaning, and transformation processes.
- Creating and managing databases within SPSS.
Working with Syntax and Automation
- Introduction to SPSS command syntax.
- Automating analyses through syntax scripts.
- Integrating SPSS with Python and R.
Descriptive Statistics and Visualization
- Measures of central tendency and dispersion.
- Standardization and z-scores.
- Creating tables, charts, and interactive visualizations.
Inferential Statistics
- Hypothesis testing and statistical significance.
- Correlation and regression analysis.
- t-tests, ANOVA, and chi-square tests.
Predictive Modeling with SPSS
- Linear and logistic regression models.
- Decision trees and classification models.
- Time series forecasting and survival analysis.
Advanced Techniques and Applications
- Factor analysis and cluster analysis.
- Handling missing values and outliers.
- Case studies in marketing, health, and social sciences.
Reporting and Sharing Results
- Formatting and customizing SPSS outputs.
- Exporting results to Word, Excel, and PDF.
- Creating professional reports to support decision-making.
Summary and Next Steps
Requirements
- Foundational knowledge of statistics and data analysis concepts (e.g., variables, hypotheses, significance).
- Familiarity with Microsoft Excel or comparable spreadsheet applications.
- Previous experience with research methods or handling datasets is advantageous but not mandatory.
Target Audience
- Analysts
- Researchers
- Scientists
- Anyone seeking practical proficiency in SPSS and predictive analytics
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
knowledge of the trainer, tailor based, all topics covered
eleni - EUAA
Course - Forecasting with R
The variation with exercise and showing.
