2017 - Webinar on Design of Experiments for Non-Statisticians

Description:
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 :
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
Areas Covered in the Session :
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