Descriptive Statistics, Sampling & Regression
Apply statistical techniques, including sampling and regression analysis to ‘real world’ case studies for data-driven decision making.
Why Does this Course Matter:
Sound statistical knowledge is essential for evidence-based decision-making. This course equips professionals to analyse and interpret data accurately—essential for drawing reliable insights in operations, strategy, planning, and reporting. It provides a practical starting point for building a robust analytical skillset that supports better outcomes in any sector.
What Will I Learn:
- Confidence in using the Normal Distribution for data interpretation and analysis
- Ability to describe key dataset features and understand their impact on results
- Skills in applying correlation and regression to explore relationships in real-world data
- Knowledge of sampling theory and how to draw meaningful conclusions from data subsets
- Foundation for more advanced analytical techniques such as forecasting and simulation
Course Topics:
- Apply the Normal Distribution to real business problems
- Perform and interpret correlation and regression analysis
- Explore practical issues with sampling and common data questions
- Understand statistical assumptions and how they affect analysis
- Use statistical results to inform forecasting, simulation, and decision support.
Who is this course for:
- Early-career Operational Researchers seeking a solid grounding in statistics
- Analysts and professionals looking to build confidence in statistical interpretation
- Those working with data in roles across business, government, or the third sector
- Project teams involved in evidence gathering, performance monitoring, or planning
- Anyone responsible for interpreting or presenting data for informed decision-making
- Individuals preparing to progress toward more advanced forecasting or simulation techniques
Related Courses
Prices
- OR Society Member £495 + VAT
- Non-Member £625 + VAT
- Student Member £370 + VAT
- For group booking discounts please contact [email protected]
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Registration
Last day to register is 16/11/2026