Design Of Experiments (Doe) 101 Methods And Analysis Seminar (ONLINE EVENT)

(MENAFN- GlobeNewsWire - Nasdaq) Design of Experiments (DoE) offers market opportunities across various sectors by enabling efficient, informed decision-making through structured variable analysis. It benefits scientists, engineers, pharma, and marketers by optimizing processes and innovations. Enhance skills in DoE through our 2-Day Virtual Seminar.

Dublin, Jan. 06, 2026 (GLOBE NEWSWIRE) -- The "Design of Experiments 101 - Methods and Analysis (Jan 29th - Jan 30th, 2026)" training has been added to ResearchAndMarkets's offering.
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.
To harness the full potential of DoE, consider attending our 2-Day Virtual Seminar on Design of Experiments. You will be provided with practical insights and demonstration of DoE models. 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

Who Should Attend:

• Research Scientists
• Laboratory Technicians
• Manufacturing Engineers
• Quality Control Specialists
• Data Analysts and Statisticians
• Product Development Managers
• Clinical Trial Coordinators
• Biostatisticians

Key Topics Covered:
DAY 1
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
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
Speaker
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.
For more information about this training visit

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