World Conference Calendar

33842 Conferences

Statistical Methods: A Visual Approach 2017

Added by globalcompliancepanel on 2017-09-06

Conference Dates:

Start Date Start Date: 2017-11-09
Last Date Last Day: 2017-11-10
Deadline for abstracts/proposals Deadline for abstracts/proposals: 2017-11-07

Conference Contact Info:

Contact Person Contact Person: Event Manager
Email Email:
Address Address: Salt Lake City, Salt Lake City, UT, United States
Phone Tel: 800-447-9407
Phone Fax: 302-288-6884

Conference Description:

Course "Statistical Methods: A Visual Approach" has been pre-approved by RAPS as eligible for up to 12 credits towards a participant's RAC recertification upon full completion.


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.

Who Will Benefit:

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


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

Read More: trol/globalseminars/~product_id=901116SE MINAR?worldconferencecalendar-November-2 017-SEO
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