Design of Experiments 101 - Methods and Analysis

SEMINAR DESCRIPTION		WHO SHOULD ATTEND
In today's data-driven world, making informed decisions is crucial for success. Design of Experiments (DoE) provides a structured approach to investigate relationships between variables, eliminating guesswork of what is important, leading to reliable outcomes. DoE enhances efficiency by allowing simultaneous examination of multiple factors, saving time and providing a comprehensive understanding of systems. Professionals across various fields greatly benefit from using DoE. Scientists and researchers can conduct rigorous experiments, engineers can optimize manufacturing processes, pharmaceutical professionals can develop new treatments, and marketers can understand consumer behavior better. Mastering DoE is essential for effective decision-making, efficiency, and innovation.		Research Scientists Laboratory Technicians Manufacturing Engineers Quality Control Specialists Data Analysts and Statisticians Product Development Managers Clinical Trial Coordinators Biostatisticians

To harness the full potential of DoE, consider attending our 2-Day Virtual Seminar on Design of Experiments. Elaine Eisenbeisz, Owner of Omega Statistics, will provide practical insights and demonstration of DOE models. Minitab statistical software will be used in the training. Whether you’re a scientist, engineer, marketer, or industry professional, this seminar will equip you with the skills to implement DoE effectively, driving success in your field.

LEARNING OBJECTIVES:

By the end of this seminar, participants will be equipped with the skills and requisite knowledge to effectively apply Design of Experiments in their work, leading to improved decision-making, efficiency, and innovation.

Foundational Knowledge: Gain an understanding of the core principles and concepts of DoE.
Experiment Planning: Develop the ability to effectively plan and design experiments, selecting appropriate variables and design types.
Data Analysis Skills: Learn to analyze experimental data using statistical software and interpret results accurately.
Practical Application: Apply DoE techniques to real-world problems, enhancing problem-solving skills and practical knowledge.
Optimization: Understand how to use DoE for process optimization, improving efficiency, and achieving better outcomes.
Best Practices: Learn best practices and strategies for implementing DoE in various professional fields.
Advanced Techniques: Explore some of the advanced DoE techniques and their applications in complex scenarios

Areas Covered:

The benefits and components of a supplier management program
Regulatory requirements for managing suppliers and contract manufacturers
Strategic decision making for good supplier management
How to manage risk and reduce the costs associated with having suppliers
The steps involved in selecting and onboarding a supplier
Developing good supplier relationships including managing improvement and nonconforming events
Writing effective and useful quality agreements
Reviewing supplier performance and making performance-based decisions
How to perform a desktop assessment and a supplier audit (and when to use each)
Managing supplier transitions

SEMINAR OBJECTIVES		WHO SHOULD ATTEND
The benefits and components of a supplier management program Regulatory requirements for managing suppliers and contract manufacturers Strategic decision making for good supplier management How to manage risk and reduce the costs associated with having suppliers The steps involved in selecting and onboarding a supplier Developing good supplier relationships including managing improvement and nonconforming events Writing effective and useful quality agreements Reviewing supplier performance and making performance-based decisions How to perform a desktop assessment and a supplier audit (and when to use each) Managing supplier transitions		Quality Assurance Personnel & Management Quality Control Personnel & Management Laboratory Supervisors Quality Engineers Procurement Professionals Drug Development Scientists Medical Device Development Scientists Supply Chain Personnel & Management

AGENDA

DAY 1 (11 AM to 5 PM)
Session 1 - Introduction to Design of Experiments

Importance and applications of DoE
Basic principles and terminology

Session 2 - Simple Comparative Experiments

Simple comparative experiments
Sample size determination and power

Coffee Break
Session 3 - Experiments with a Single Factor (One-way ANOVA)

One-factor experiments with multiple levels
Multiple comparisons and random effects models

Lunch Break
Session 4 - Blocking Designs

Randomized complete block designs (RCBD)
Latin square designs and their extensions
Q&A Session

DAY 2 (11 AM to 5 PM)
Session 5 - Factorial Designs

Factorial designs with two treatment factors
Main effects and interactions

Session 6 - Factorial Designs

Simplest case and estimated effects
2k factorial designs

Coffee Break
Session 7 - Advanced Experimental Designs

Fractional factorial designs
Response surface methodology (RSM)

Lunch Break
Session 8 – Regression Analysis in DoE

Regression analysis
Q&A and Closing Remarks

Course Director: ELAINE EISENBEISZ

Elaine Eisenbeisz is a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California. Elaine has over 30 years of experience in creating data and information solutions for industries ranging from governmental agencies and corporations, to start-up companies and individual researchers.

Elaine’s love of numbers began in elementary school where she placed in regional and statewide mathematics competitions. She attended University of California, Riverside, as a National Science Foundation scholar, where she earned a B.S. in Statistics with a minor in Quantitative Management, Accounting. Elaine received her Master’s Certification in Applied Statistcs from Texas A&M, and is currently finishing her graduate studies at Rochester Institute of Technology. Elaine is a member in good standing with the American Statistical Association as well as many other professional organizations. She is also a member of the Mensa High IQ Society. Omega Statistics holds an A+ rating with the Better Business Bureau.

Elaine has designed the methodology for numerous studies in the clinical, biotech, and health care fields. She currently is an investigator on approximately 10 proton therapy clinical trials for Proton Collaborative Group, based in Illinois. She also designs and analyzes studies as a contract statistician for nutriceutical and fitness studies with QPS, a CRO based in Delaware. Elaine has also worked as a contract statistician with numerous private researchers and biotech start-ups as well as with larger companies such as Allergan and Rio Tinto Minerals. Not only is Elaine well versed in statistical methodology and analysis, she works well with project teams. Throughout her tenure as a private practice statistician, she has published work with researchers and colleagues in peer-reviewed journals. Please visit the Omega Statistics website at www.OmegaStatistics.com to learn more about Elaine and Omega Statistics.