Statistical Analysis for Process and Product Development: 2-Day In-person Seminar

By: Steven Wachs, VP and Principal Statistician
Location :- Troy, MI | Thursday, January 24, 2019 | Friday, January 25, 2019

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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

Course Outline

Day One (8:30 AM – 4:30 PM)
  • 8:30 – 9:00 AM: Registration
  • 9:00 AM: Session Start Time
  • Basic Statistics & Distributions
    • Data Types
    • Populations & Samples
    • Central Tendency and Variation
    • Probability Distributions
    • The Normal Distribution
  • Graphical Analysis
    • Pareto Charts
    • Run Charts
    • Boxplots and Individual Value Plots
    • Histograms
    • Scatter Plots
  • Hypothesis Testing Concepts
    • Test Statistics, Crit. Values, p-values
    • One and Two Sided Tests
    • Type I and Type II Errors
    • Estimation and Confidence Intervals
  • Hypothesis Tests for One and Two Groups
    • Testing Means (1 sample t ,2 sample t and paired t tests)
    • Testing Variances (Chi-Square, F test)
    • Testing Proportions (overview)
    • Tolerance Intervals
    • Equivalence Tests
  • Hypothesis Tests for Multiple (>2) Groups
    • Testing Means (ANOVA)
    • Multiple Comparisons
    • Testing Variances (Bartlett’s and Levene’s Test)
    • Testing for Normality
Day Two (8:30 AM – 4:30 PM)
  • Power & Sample Size
    • Type II Errors and Power
    • Factors affecting Power
    • Computing Sample Sizes
    • Power Curves
    • Sample Sizes for Estimation
  • Introduction to Experimental Design
    • What is DOE?
    • Definitions
    • Sequential Experimentation
    • When to use DOE
    • Common Pitfalls in DOE
  • A Guide to Experimentation
    • Planning an Experiment
    • Implementing an Experiment
    • Analyzing an Experiment
    • Case Studies
  • Two Level Factorial Designs
    • Design Matrix and Calculation Matrix
    • Calculation of Main & Interaction Effects
    • Interpreting Effects
    • Using Center Points
  • Identifying Significant Effects
    • Determining which effects are statistically significant
    • Analyzing Replicated and Non-replicated Designs
  • Developing Mathematical Models
    • Developing First Order Models
    • Residuals /Model Validation
    • Optimizing Responses

Meet Your Instructor

Steven-Wachs_90x112
Steven Wachs
Principal Statistician, Integral Concepts, Inc

Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.

Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty.

Venue

Location :
Troy, MI (Venue to be announced shortly)

January 24-25, 2019
Register Online

Register Online

$1,299

Seminar One Registration

January 24-25, 2019, Troy, MI
(Registrations till December 15, 2018 - $1299)
(Registrations after December 15, 2018 - $1699)

Early bird seats are limited and based on first-come, first-serve.

Your registration fee includes the workshop, all course materials and lunch.
For discounts on multiple registrations, contact customer care at +1-1-888-771-6965.

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Your Registration for the seminar is subject to following terms and conditions. If you need any clarification before registering for this seminar please call us @ +1-888-771-6965 or email us @ editor@grcseminars.com

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Payment is required before 2 days of the date of the conference. We accept American Express, Visa and MasterCard. Make checks payable to MetricStream Inc. ( our parent company)

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Written cancellations through fax or email (from the person who has registered for this conference) received at least 10 calendar days prior to the start date of the event will receive a refund — less a $300 administration fee. No cancellations will be accepted — nor refunds issued — within 10 calendar days from the start date of the event.

On request by email or fax (before the seminar) a credit for the amount paid minus administration fees ($300) will be transferred to any future GRC Seminars event and a credit note will be issued.

Substitutions may be made at any time. No-shows will be charged the full amount.

We discourage onsite registrations, however if you wish to register onsite payment to happen through credit card immediately or check to be submitted onsite. Conference material will be given on the spot if it is available after distributing to other attendees. In case it is not available we will send the material after the conference is over.

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