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Design of Experiments for Non-Statisticians

Date | Oct 12, 2018 |
Time | 03:00 PM EDT |
Cost | $200.00 |
Online
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The solution of many Pharma and Biotech problems include the collection, analysis, interpretation and presentation of data. The use of design of experiments in the form of two-level factorial and fractional-factorial designs increases the probability of finding an acceptable solution to the problem. One reason DOE is not used more is the perception that sophisticated statistical methods are required to effectively use DOE. This webinar shows that this perception is without basis and shows how to do DOE with minimal calculations.
You will Learn How to :
Who Will Benefit:
You will Learn How to :
- Get started in using DOE to solve problems
- Utilize the foundations and principles of DOE
- Design, analyze, interpret and present the results of factorial experiments
- Simultaneously experiment with quantitative and qualitative variables
- Develop cause and effect relationships and the associated prediction models
- Basics of data-based problem solving
- Why DOE works
- What’s wrong with one-factor-at-a-time strategy
- Factorial experiment designs for 2, 3, 4, 5 and more factors
- Screening experiments using fractional-factorial and Plackett-Burman designs
- Roadmap for the analysis of factorial experiments
- Calculation and graphical display of factor effects
- Tips, Traps and Tools of the problem solver
Who Will Benefit:
- R&D Departments
- Manufacturing Departments
- Quality Assurance Departments
- Quality Control Departments
- Regularly Affairs Departments
- Financial Analysts
- Scientists
- Engineers
- Everyone who collects, analyzes and presents data to solve problems and make improvements
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