Course Name:
Aviation Statistical Analysis and Forecasting Techniques
Date:11/05/2025 - 15/05/2025
Location:Live sessions
Conducted By:
RTC
How Will I Benefit?
- Understand the role of statistical analysis in aviation decision-making processes.
- Develop skills in using statistical tools to analyze aviation data (e.g., traffic, operational performance).
- Learn how to apply forecasting techniques to predict future air traffic demand.
- Assess the accuracy and reliability of aviation forecasts.
- Gain insight into the ICAO’s data collection and reporting standards.
- Apply data-driven decision-making to improve airport, airline, and air transport management.
- Interpret ICAO & ACI statistical forms,
Who Should Attend?
- Airport and airline operations managers looking to enhance decision-making through data analysis.
- Aviation regulatory authorities involved in traffic management and forecasting.
- Aviation planners and forecasters involved in future traffic and operational capacity planning.
- Data analysts and statisticians working in aviation companies or regulatory bodies.
- Professionals from civil aviation authorities responsible for reporting and monitoring data.
- Aviation consultants and researchers who work on strategic planning and forecasting projects.
Course Contents:
- Introduction to aviation data sources (ICAO databases, IATA statistics, etc.).
- Air Transport principles & ICAO statistics program,
- ICAO & ACI forms,
- Forecasting techniques in the air transport industry,
- Linear and multiple regression techniques,
- Statistical methods for analyzing air traffic, airline performance, and airport operations.
- Time series analysis and forecasting models in aviation (e.g., ARIMA, exponential smoothing).
- Scenario-based forecasting for traffic demand and capacity planning.
- Applications of statistical analysis in aviation safety, security, and environmental performance.
- Case studies of real-world applications of aviation statistical analysis and forecasting
Fees
Members:USD
1250
Non Members:USD
1400