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Seminar on Statistical Methods: A Visual Approach  

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Global Compliance Panel   


Data Analysts, Research Scientists, Quality Professionals, Regulatory/Compliance Professionals, Laboratory Managers, HR Professionals, Project Managers, Design and Development Engineers, Software Engineers, Process Owners, Quality Engineers, Quality Auditors, Medical Affairs Professionals, Process Scientists/Engineers


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Training Course Syllabus:


An essential task in any compliance analytics workflow is to not only explore your data visually, but also to communicate your results professionally with graphic displays. Do you have the tools and skills to quickly and thoroughly perform these tasks? This course in data visualization will present methods to allow you to interactively discover relationships graphically. We will provide the foundations for creating better graphical information to accelerate the insight discovery process and enhance the understandability of reported results. First principles and the "human as part of the system" aspects of information visualization from multiple leading sources such as Harvard Business Review, Edward Tufte, and Stephen Few will be explored using representative example data sets. We will discuss best practices for graphical excellence to most effectively, clearly, and efficiently communicate your story. We will construct visualizations for univariate, multivariate, time-dependent, and geographical data. Participants are encouraged to bring laptops to follow along demonstrations in JMP (free trial download at, and open source solutions such as R ( and Tableau Public (

Why you should attend:

Data-driven decisions across all regulated industries are now expected. Compliance regulations require analytic solutions that begin with data visualization for discovering relationships and finish with crisp graphs communicating results. As an example, 21 CFR and guidance documents for the pharmaceutical, biopharmaceutical, and medical device industries specify the application of statistical methods for: setting validation criteria and specifications, performing measurement systems analysis (MSA), conducting stability analysis, using design of experiment (DOE) for process development and validation, developing process control charts, and determining process capability indices. Data visualization is the foundation for each one of these areas. In some cases, graphical plots and tables alone may sufficiently address compliance criteria as is the case for the FDA analytical requirements for third-tier critical to quality attributes for analytical biosimilarity evaluations. Data visualization is also essential in other areas such as HIPAA compliance, risk management and analysis, and many other of the quality functions.


Day 1 Schedule

Lecture 1:

Introduction and definitions
Examples of data visualizations for compliance and regulated industries
Historical context
Characteristics of data
Interactive data visualization exploration with Excel and websites
Lecture 2:

Human side of data visualization
Principles of good graphic design
Data visualization methodology
Best practices
Lecture 3:

Software introduction: JMP
Univariate plots
Distributions and histograms
Pie graphs, violin plots, pareto plots, box plots
Conditional formatting
Lecture 4:

Mulitvariate plots and heatmaps
Multivariate scatterplots and density graphs
Contour plots
Categorical data plots: treemaps, mosaic plots

Day 2 Schedule

Lecture 1:

Software introduction: R
Software introduction: Tableau Public
Univariate plots with R and Tableau
Multivariate plots with R and Tableau
Lecture 2:

Dynamic and interactive graphs
Brushing, dynamic linking, and filtering
Profilers on response variables and optimization
Lecture 3:

Time series plots
Waterfall plots
Sparklines and trend lines
Statistical Process Control charts
Lecture 4:

Text data visualization
Course summary

Speaker: James Wisnowski

James Wisnowski is the cofounder of Adsurgo LLC and co-author of the book Design and Analysis of Experiments by Douglas Montgomery: A Supplement for using JMP. He has over 25 years of experience and currently provides training and consulting services to industry and government in Design of Experiments (DOE), Reliability Engineering, Data Visualization, Predictive Analytics, and Text Mining. Dr. Wisnowski has been an invited speaker on applicability of statistics for national and international conferences. Prior to his current position, he was a senior program manager for URS, Chief of the Statistics Division in the Mathematics Department at the Air Force Academy, and a retired military officer. He is currently a member of the editorial board of Quality Engineering and has published numerous international refereed journal articles on statistics. Jim has a PhD in Industrial Engineering from Arizona State University.

Seminar Summary:

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