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Statistical Analysis for Process and Product Development


Thursday, October 27, 2016 at 8:30 AM - Friday, October 28, 2016 at 4:30 PM (PDT)

Statistical Analysis for Process and Product Developmen...

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Ticket Type Sales End Price Fee Quantity
Seminar One Registration (Early bird price)
For Registrations after August 10, 2016 - 1,899
Oct 27, 2016 $1,499.00 $0.00
Seminar One Registration Oct 27, 2016 $1,899.00 $0.00

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Course Description:

This course is designed to help scientists and engineers apply statistical methods used assist decision making in process and product development. Variability must be considered when utilizing data to arrive at conclusions.

  • This course will cover Basic Statistics and Graphical Methods used to summarize data.
  • You will learn how to apply Hypothesis Testing methods to determine whether groups are statistically equivalent or not with respect to key process characteristics such as process averages and variability.
  • The use of confidence intervals when estimating key parameters will be covered.
  • When planning studies, sample size determination is critical to ensure that study results will be meaningful. Methods to determine appropriate sample sizes for various types of problems will be covered.
  • Finally, an introduction to Design of Experiments (DOE) is provided. DOE is an extremely efficient method to understand which variables (and interactions) affect key outcomes and allows the development of mathematical models used to optimize process and product performance. The concepts behind DOE are covered along with some effective types of screening experiments. Case studies will also be presented to illustrate the use of the methods.

This highly interactive course will allow participants the opportunity to practice applying statistical methods with various data sets. The objective is to provide participants with the key tools and knowledge to be able to apply the methods effectively in their process and product development efforts.

Course Information:

Participants are requested to bring a laptop with Minitab Version 17 software installed.

Learning Objectives:

  • Effectively summarize data and communicate results with basic statistics and graphical techniques
  • Apply Hypothesis Testing to test whether two or more groups of data are statistically equivalent or not.
  • Estimate key process parameters with associated confidence intervals to express estimate uncertainty
  • Determine appropriate sample sizes for estimation and hypothesis testing
  • Understand key concepts related to Design of Experiments
  • Apply experiments to determine cause and effect relationships and model process behaviour


Who will Benefit:

  • Scientists
  • Product and Process Engineers
  • Quality Engineers
  • Personnel involved in product development and validation


For Registration          


Note: Use coupon code NB5SQH8N and get 10% off on registration.

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When & Where

San Francisco

San Francisco, CA

Thursday, October 27, 2016 at 8:30 AM - Friday, October 28, 2016 at 4:30 PM (PDT)

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Enhancing global compliance, creating a world where quality and compliance professionals, regulators, and government agencies come together to help the world comply with the intent and the spirit of laws, policies and mandates, ensuring continuous improvement in global operations, quality & safety.

Making sure that we are responsible corporate citizens helping our constituents build a more responsible enterprise, one which operates with high quality , under a code of ethics, and with process discipline to ensure greater shareholder returns.

Keeping things simple and straight forward , so that we all can indeed improve the quality of our processes, our work, our businesses and enhance compliance globally.

Being inclusive, giving the process experts ( & novices! ), compliance professionals, quality champions, and regulatory agencies a voice so that all of us can contribute and make a difference.

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Statistical Analysis for Process and Product Development
Things to do in San Francisco, CA Conference Science & Tech

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