Validation work depends on statistics, but you don't need to be a statistician to use the core tools well. This 60-minute validation statistics webinar explains the common techniques through real-world examples and an interactive exercise.
You'll start with what statistics is, why validation needs it and what regulators expect. The session then focuses on variance: where it comes from, how to measure it, normal and non-normal distributions, and how to express it with variance, standard deviation and the coefficient of variation.
It finishes with process capability: whether your system can do what you need, how to measure capability and how to use it to set acceptance criteria for validation.
WHY SHOULD YOU ATTEND?
Anyone involved in validation needs a basic understanding of statistics and how it applies to their work. Without it, acceptance criteria and conclusions are harder to justify.
This session suits validation engineers, R&D and technical support scientists, quality assurance and regulatory affairs professionals, and production staff involved in validation in the medical device and pharmaceutical industries.
AREA COVERED
Introduction
- What statistics is
- Why validation needs statistics
- Regulatory expectations
The concept of variance
- Why variance matters
- Sources of variance
- Measuring variance
- Normal and non-normal distributions
Expressing variance
- Variance
- Standard deviation
- Interactive exercise: measuring variance
- Coefficient of variation
Process capability
- Can your system do what you need it to do?
- Measuring capability
- Using capability to set acceptance criteria for validation
Conclusion and discussion
LEARNING OBJECTIVES
- Explain why statistics is needed in validation and what regulators expect
- Identify sources of variance and measure it
- Tell normal from non-normal distributions
- Express variance using variance, standard deviation and coefficient of variation
- Assess whether a process is capable of meeting requirements
- Use process capability to set validation acceptance criteria
WHO WILL BENEFIT?
- Quality Assurance Professionals
- R&D Scientists
- Technical Support Scientists
- Regulatory Affairs Professionals
- Manufacturing and Production Personnel involved in validation activities
Anyone involved in validation needs a basic understanding of statistics and how it applies to their work. Without it, acceptance criteria and conclusions are harder to justify.
This session suits validation engineers, R&D and technical support scientists, quality assurance and regulatory affairs professionals, and production staff involved in validation in the medical device and pharmaceutical industries.
Introduction
- What statistics is
- Why validation needs statistics
- Regulatory expectations
The concept of variance
- Why variance matters
- Sources of variance
- Measuring variance
- Normal and non-normal distributions
Expressing variance
- Variance
- Standard deviation
- Interactive exercise: measuring variance
- Coefficient of variation
Process capability
- Can your system do what you need it to do?
- Measuring capability
- Using capability to set acceptance criteria for validation
Conclusion and discussion
- Explain why statistics is needed in validation and what regulators expect
- Identify sources of variance and measure it
- Tell normal from non-normal distributions
- Express variance using variance, standard deviation and coefficient of variation
- Assess whether a process is capable of meeting requirements
- Use process capability to set validation acceptance criteria
- Quality Assurance Professionals
- R&D Scientists
- Technical Support Scientists
- Regulatory Affairs Professionals
- Manufacturing and Production Personnel involved in validation activities
