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Throughout 21 CFR and guidance documents for the pharmaceutical, biopharmaceutical, and medical device industries, the application of statistical methods are specified for: performing measurement systems analysis (MSA), using design of experiment (DOE) for process development and validation, developing process control charts, and determining process capability indices.

Different statistical methods are required for each of these particular applications. Data and tolerance intervals are common tools used for setting acceptance criteria and specifications. Simple linear regression and analysis-of-covariance (ANCOVA) are used for setting expiries and conducting stability analysis studies. Two-sample hypothesis tests, analysis-of-variance (ANOVA), regression, and ANCOVA are methods used for analyzing designed experiment for process development and validation studies. Descriptive statistics (distribution, summary statistics), run charts, and probability (distributions) are used for developing process control charts and developing process capability indices.

This course provides instruction on how to apply the appropriate statistical approaches: descriptive statistics, data intervals, hypothesis testing, ANOVA, regression, ANCOVA, and model building. Once competence in each of these areas is established, select industry-specific applications are presented for the participants: MSA, DOE, SPC, and process capability.

Seminar Fee Includes:
Lunch
AM-PM Tea/Coffee
Seminar Material
USB with seminar presentation
Hard copy of presentation
Attendance Certificate
$100 Gift Cert for next seminar

Learning Objectives:

Upon completing this course participants should be able to:

  • describe and analyze a distribution of data
  • develop summary statistics
  • generate and analyze statistical intervals and hypothesis tests to make data-driven decisions
  • describe the relationship between and among two or more factors or responses
  • understand issues related to sampling and calculate appropriate sample sizes
  • use statistical intervals: confidence, prediction, and tolerance
  • understand how Measurement Systems Analysis (MSA) can be to estimate variance associated with: repeatability, intermediate precision, and reproducibility
  • understand how design of experiments (DOE) is used in process development
  • understand what it means for a process to be in (statistical) control and capable

Who will Benefit:

This webinar is designed for scientists and engineers who are involved with product and/or process design as well as manufacturing:

  • Process Scientist/Engineer
  • Design Engineer
  • Manufacturing Engineer
  • R&D Scientist
  • Product Development Engineer
  • Regulatory/Compliance Professional
  • Design Controls Engineer
  • Six Sigma Green Belt
  • Six Sigma Black Belt
  • Continuous Improvement Manager
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Day 01(8:30 AM - 4:30 PM)
  • 08.30 AM - 09.00 AM: Registration
  • 09.00 AM: Session Start
  • Basic Statistics
    • sample versus population
    • descriptive statistics
    • describing a distribution of values
  • Intervals
    • confidence intervals
    • prediction intervals
    • tolerance intervals
  • Hypothesis Testing
    • introducing hypothesis testing
    • performing means tests
    • performing normality tests
  • ANOVA
    • defining analysis of variance and other terminology
    • discussing assumptions and interpretation
    • interpreting hypothesis statements for ANOVA
    • performing one-way ANOVA
Day 02(8:30 AM - 4:30 PM)
  • Regression
    • producing scatterplots and performing correlation
    • performing simple linear regression
  • Model Building
    • introduction
    • performing N-way ANOVA
    • performing multiple linear regression
    • performing ANCOVA
  • Applied Statistics
    • introduction to Measurement Systems Analysis (MSA)
    • introduction to design of experiments (DOE)
    • introduction to process control and capability
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Heath Rushing

Heath Rushing
Principal Consultant, Adsurgo LLC

Heath Rushing is the cofounder of Adsurgo and author of the book Design and Analysis of Experiments by Douglas Montgomery: A Supplement for Using JMP. Previously, he was the JMP and Six Sigma training manager at SAS. He led a team of nine technical professionals designing and delivering applied statistics and quality continuing education courses. He has created tailored courses, applications, and long-term training plans in quality and statistics across a variety of industries to include biotech, pharmaceutical, medical device, and chemical processing.

Mr. Rushing has been an invited speaker on applicability of statistics for national and international conferences. As a quality engineer at Amgen, he championed statistical principles in every business unit. He designed and delivered a DOE course that immediately became the company standard required at multiple sites. Additionally, he developed and implemented numerous innovative statistical methods advancing corporate risk management, process capability, and validation acceptance criteria. He won the top teaching award out of 54 instructors in the Air Force Academy math department where he taught several semesters and sections of operations research and statistics. Additionally, he designs and delivers short courses in statistics, data mining, and simulation modeling for SAS.

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Seminar One Registration

November 9-10, 2017, San Francisco, CA
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(For Registrations till September 20, 2017 - $1499)
(For Registrations till October 20, 2017 - $1599)
(For Registrations after October 20, 2017 - $1699)

$2,099.00

Seminar One Registration (With 2 Nights Stay)

November 9-10, 2017, San Francisco, CA

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Location:

San Francisco, CA
(Venue to be announced shortly)

November 9-10, 2017

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