Become Better With Biostatistics for the Non-Statistician In 10 Minutes

That statistics can be a vital decision-making tool for clinical research is well-established. It is helpful for the clinician in situations where a p-value can help determine the next steps in the development of a drug or procedure. It is thus vital for decision makers to comprehend the theory and application of statistics.

We have many statistical software applications that help in arriving at crucial decisions. However, almost all these software applications were developed for statisticians. These software applications could confound the non-statisticians. Their confusion could start with something as basic as even knowing which key to press.

In this scenario, learning how to use biostatistics and derive its benefits is important. A marathon, six-hour webinar being organized by GlobalCompliancePanel, a leading provider of professional trainings for all the areas of regulatory compliance, on October 25, will explain biostatistics for the non-statistician.

Elaine Eisenbeisz, a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California, will be the expert at this webinar. Please visit https://www.globalcompliancepanel.com/virtual-seminar/6-hour-virtual-seminar-on-biostatistics-for-the-non-statistician-10307LIVE to register for this webinar.

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This webinar, designed for non-statisticians, provides a non-mathematical introduction to biostatistics. Elaine will arm the participants with all the information and skills necessary for understanding statistical concepts and findings as they apply to clinical research, and to confidently convey this knowledge to people with whom they work.

This webinar will emphasize statistical concepts, application, and interpretation, and not on mathematical formulas or actual data analysis. Participants are expected to have an elementary understanding of statistics, but this is not mandatory.

It is aimed at professionals who must understand and work with study design and interpretation of findings in a clinical or biotechnology setting.

This will be the agenda that will be covered at this webinar:

Why Statistics?

• Do we really need statistical tests?
• Sample vs. Population
• I’m a statistician not a magician! What statistics can and can’t do
• Descriptive statistics and measures of variability

The many ways of interpretation

• Confidence intervals
• p-values
• effect sizes
• Clinical vs. meaningful significance

Common Statistical Tests

• Comparative tests
• Regression analysis
• Non-parametric techniques

Bayesian Logic

• A different way of thinking
• Bayesian methods and statistical significance
• Bayesian applications to diagnostics testing
• Bayesian applications to genetics

Interpreting Statistics – Team Exercise

• Team Exercise: Review a scientific paper and learn how to
  • Interpret statistical jargon
  • Look for reproducibility, transparency, bias, and limitations
  • Convey information coherently to non-statisticians

Study power and sample size

• Review of p-value, significance level, effect size
• Formulas, software, and other resources for computing a sample size

Developing a Statistical Analysis Plan

• Using FDA guidance as a foundation, learn the steps and criteria needed to develop a statistical analysis plan (SAP).
• An SAP template will be given to all attendees.

Specialized topics/Closing Comments/Q&A

• Comparing Survival Curves
• Pharmacokinetics/Pharmacodynamics (PK/PD)
• Taking a holistic view to study design and interpretation
• Question and Answer session.

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About the Director:

Elaine brings over 30 years of experience in creating data and information solutions for industries ranging from governmental agencies and corporations to start-up companies and individual researchers. She has designed the methodology for numerous studies in the clinical, biotech, and health care fields.

She currently is an investigator on approximately 10 proton therapy clinical trials for Proton Collaborative Group, based in Illinois. She also designs and analyzes studies as a contract statistician for nutraceutical and fitness studies with QPS, a CRO based in Delaware.

GlobalCompliancePanel to organize two-day seminar on “FDA and U.S. Customs Import Rules and Export Traps in 2020”

GlobalCompliancePanel, a leading provider of professional training for all the areas of regulatory compliance, is organizing a two-day, in person, live seminar on the topic, “FDA and U.S. Customs Import Rules and Export Traps in 2020”, on December 4 and 5.

Casper Uldriks, an ex-FDA Expert and former Associate Center Director of CDRH, will be the Director of this seminar. Please enroll for this session by visiting https://www.globalcompliancepanel.com/seminar/tougher-import-rules-for-FDA-901966SEMINAR

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Smarter, more sophisticated, more agile and more demanding. These are what the FDA and the Customs and Border Patrol Service (CBP) have become of late when it comes to their expectations and requirements from importing firms of the submission of information and adherence to government procedures. Firms that fail to properly execute an import and export program can expect the FDA and the CBP to delay, detain or refuse their shipments.

The new Automated Commercial Environment (ACE) computer program from the CBP has brought in many changes to the process of import logistics and information reporting for FDA regulated products. As a result, companies that do not comply with the requirements set out in the ACE program can experience one of the worst nightmares they can think of: having their shipment stopped before it is even loaded at the foreign port! And then, if they refuse to or fail to use the ACE program, such ships also carry a fine of up to $10,000 for every offense.

There is more: such companies whose products the FDA detains face a cumbersome, long winding and expensive legal process. The FDA expects companies to have the import coding information accurate and up-to-date. Any company that lacks a thorough and clear understanding of the automated and human review process are almost certain to have their shipments detained.

And then, what happens in a scenario in which the FDA decides that importers should bring the products back to the port of entry after they received a release but cannot locate the product that has been sold? Well, in such instances, such companies are slapped a fine that is three times the value of the shipment, not to speak of the additional adverse legal concerns and strategies that come along.

What do all these mean? Simple: if you are an importer, you are doomed if you fail to comply with the FDA’s guidelines on imports.

Yet, there is a way out of this quagmire, in the form of the Voluntary Qualification Importer Program, which the FDA is implementing under the FDA Food Safety and Modernization Act. This plan seeks to reward importers who demonstrate a level of confidence about the quality of food they import by establishing an FDA-supervised, fee-based program. What this program does is that it facilitates the review and importation of foods from importers who establish a higher level of control over the safety and supply chain aspects of the imported food items.

And then, there is also the extra perk that the FDA offers: its export certificates. Offered at a reasonable fee; these certificates can go a long way in giving an importer a competitive advantage in foreign markets. In fact, a few foreign governments make an FDA export certificate a requirement.

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The aim of this seminar is to offer learning on all these core areas of the FDA and US Customs Import Rules in 2020. The Director will explain how to deal with common problems, such as returns for repair, importing QC samples, and investigational products. The learning will be taught over the following agenda:

Day 1 Schedule

Lecture 1:

FDA Legal Authority Customs and Border Control (CBP) Import Process FDA Import Process Registration and documentation

Lecture 2:

FDA Import Process (continued)

• Import Brokers
• Prior Notice Information
• CBP and FDA computer programs
• Import Codes
• Bonds and Bonded Warehouses
• FDA “Notice of Action”

Lecture 3:

Import Delays Import Alerts Detention Refusals

Day 2 Schedule

Lecture 1:

Foreign Inspections FDA 483 – Inspectional Observations

Lecture 2:

FDA Warning Letters and Automatic detention

Lecture 3:

Import Hypothetical FDA Import for Export Program FDA Export Program Export Hypothetical

Lecture 4:

FDA Export Program Special Import Issues

• Trade Shows
• Personal Use
• Compassionate Use

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https://www.fda.gov/Food/GuidanceRegulation/GuidanceDocumentsRegulatoryInformation/ucm448728.htm

Best Biostatistics Tips You Will Read This Year

Statistics is a useful decision making tool in the clinical research arena. When working in a field where a p-value can determine the next steps on development of a drug or procedure, it is imperative that decision makers understand the theory and application of statistics.

Many statistical softwares are now available to professionals. However, these softwares were developed for statisticians and can often be daunting to non-statisticians. How do you know if you are pressing the right key, let alone performing the best test?

This seminar provides a non-mathematical introduction to biostatistics and is designed for non-statisticians. And it will benefit professionals who must understand and work with study design and interpretation of findings in a clinical or biotechnology setting.

The focus of the seminar is to give you the information and skills necessary to understand statistical concepts and findings as applies to clinical research, and to confidently convey the information to others.

Emphasis will be placed on the actual statistical (a) concepts, (b) application, and (c) interpretation, and not on mathematical formulas or actual data analysis. A basic understanding of statistics is desired, but not necessary.

• Physicians
• Clinical Research Associates
• Clinical Project Managers/Leaders
• Sponsors
• Regulatory Professionals who use statistical concepts/terminology in reporting
• Medical Writers who need to interpret statistical reports

How to interpret and use more than just a standard tool-box

How to apply statistics to manage risks and verify/validate processes in R&D, QA/QC, and Manufacturing, with examples derived mainly from the medical device design/manufacturing industry. The flow of topics over the 2 days is as follows:

• ISO standards and FDA/MDD regulations regarding the use of statistics.
• Basic vocabulary and concepts, including distributions such as binomial, hypergeometric, and Normal, and transformations into Normality.
• Statistical Process Control
• Statistical methods for Design Verification
• Statistical methods for Product/Process Qualification
• Metrology: QC Sampling Plans the statistical analysis of measurement uncertainty, and how it is used to establish QC specifications
• How to craft “statistically valid conclusion statements” (e.g., for reports)
• Summary recommendations

The various statistical methods used to support such activities can be intimidating. If used incorrectly or inappropriately, statistical methods can result in new products being launched that should have been kept in R&D; or, conversely, new products not being launched that, if analyzed correctly, would have met all requirements. In QC, mistakenly chosen sample sizes and inappropriate statistical methods may result in purchased product being rejected that should have passed, and vice-versa.

This provides a practical approach to understanding how to interpret and use more than just a standard tool-box of statistical methods; topics include: Confidence intervals, t-tests, Normal K-tables, Normality tests, Confidence/reliability calculations, Reliability plotting (for extremely non-normal data), AQL sampling plans, Metrology (i.e., statistical analysis of measurement uncertainty ), and Statistical Process Control. Without a clear understanding and correct implementation of such methods, a company risks not only significantly increasing its complaint rates, scrap rates, and time-to-market, but also risks significantly reducing its product and service quality, its customer satisfaction levels, and its profit margins.

• FDA, ISO 9001/13485, and MDD requirements related to statistical methods
• How to apply statistical methods to manage product-related risks to patient, doctor, and the designing/manufacturing company
• Design Control processes (verification, validation, risk management, design input)
• QA/QC processes (sampling plans, monitoring of validated processes, setting of QC specifications, evaluation of measurement equipment)
• Manufacturing processes (process validation, equipment qualification)

• QA/QC Supervisor
• Process Engineer
• Manufacturing Engineer
• QC/QC Technician
• Manufacturing Technician
• R&D Engineer

Dont skip this with out reading fully

Auditing Analytical Laboratories for FDA Compliance

There are two phases to this topic. The first is auditing itself. Good audits are well structured. They must consider the reasons for the audit, the regulatory requirements, as well as the nature of the laboratory being audited. We will discuss the considerations that must be made when auditing a laboratory. The social interactions that must be expected, the nature of the regulatory requirements and the nature of work that the laboratory performs will be discussed.

The second phase considers what must be considered during the audit itself. Audits conducted by inexperienced or ignorant auditors are often worthless, wasting the time and money of both the auditors and the laboratory being audited. Auditors who are familiar with laboratory operations are needed as it is easy to be fooled into thinking that a non-compliant laboratory is operating normally. Different types of laboratories will require different auditor/specialists. We will discuss the pitfalls that auditors can fall into, and what questions laboratories may expect to encounter.

It is necessary for a company to know if an analytical laboratory is capable of operating in compliance with GMP or other regulations. This is especially critical if the laboratory is a quality control laboratory whose test results will be used to support the release of a product to the public or to support and application for permission to market a product.  The failure of a quality control laboratory to comply with regulations can result in the failure of a request for permission to market a product or a forced recall of a marketed product.

In extreme cases a revocation of the permission to market a product may be the result. In any case the inability to conform to regulations will result in a loss of confidence in the ability of the manufacturer to produce a product that meets quality and regulatory requirements, and, in turn, lead to a refusal to purchase a product.

It is critical that the audit of the laboratory be conducted in a professional manner, as a poor audit will waste money and lead to a false confidence in the abilities of the audited laboratory whether it is internal or external to the company.

• Potential Auditors
• Supervisors who must initiate Audits
• Laboratory Supervisors and Workers
• Quality Assurance and Control Supervisors and Lead Workers
• Supervisory Management who must select Contractors
• Managers
• Directors
• Vice Presidents who Supervise Quality Assurance
• Quality Control
• Regulatory Affairs Groups

Top benefits from this

200+ followers. WOWWWWWW…

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we are so incredibly thankful for each and every one of you who follows and comments on my blog posts. Please know that!

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It is important for non-statisticians to become familiar with biostatistics

Statistics is extremely useful as a decision-making tool in the clinical research arena. In areas such as working in a field where a p-value can determine the next steps on development of a drug or procedure, it is very handy, because of which it is imperative for decision makers to understand the theory and application of statistics.

Many statistical software applications have now been developed and made available to professionals. It needs to be borne in mind that these software applications were developed for statisticians, because of which its use can baffle non-statisticians. Their confusions could be as basic as pressing the right key, let alone performing the best test.

A full learning session on biostatistics for the non-statistician

A seminar from GlobalCompliancePanel, a leading provider of professional trainings for all the areas of regulatory compliance, will throw light on the importance of biostatistics for the non-statistician.

Elaine Eisenbeisz, a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California, who has over 30 years of experience in creating data and information solutions for industries ranging from governmental agencies and corporations to start-up companies and individual researchers; will be the Director of this seminar.

Want to understand the importance of biostatistics for the non-statistician? Then, please enrol for this seminar by visiting It is important for non-statisticians to become familiar with biostatistics. This seminar has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion.

Statistical concepts in clinical research

Designed essentially for non-statisticians; this seminar provides a non-mathematical introduction to biostatistics. It will be of high value to professionals who must understand and work with study design and interpretation of findings in a clinical or biotechnology setting.

Elaine will equip participants of this seminar with the information and skills necessary to understand statistical concepts and findings as they relate to clinical research. With this information, they will be able to confidently communicate with people with whom they need to.

Elaine will place emphasis on the actual statistical concepts, application, and interpretation. She will not go into the areas of mathematical formulas or actual data analysis. A basic understanding of statistics is desired from the participants, but is not necessary.

This course on biostatistics for the non-statistician will help professionals involved in this area, such as Physicians, Clinical Research Associates, and Clinical Project Managers/Leaders, Sponsors, Regulatory Professionals who use statistical concepts/terminology in reporting, and Medical Writers who need to interpret statistical reports.

Elaine’s agenda for this two-day seminar will consist of the following:

Why Statistics?

• Do we really need statistical tests?
• Sample vs. Population
• I’m a statistician not a magician! What statistics can and can’t do
• Descriptive statistics and measures of variability

The many ways of interpretation

• Confidence intervals
• p-values
• effect sizes
• Clinical vs. meaningful significance

Common Statistical Tests

• Comparative tests
• Regression analysis
• Non-parametric techniques

Bayesian Logic

• A different way of thinking
• Bayesian methods and statistical significance
• Bayesian applications to diagnostics testing
• Bayesian applications to genetics

Interpreting Statistics – Team Exercise

• Team Exercise: Review a scientific paper and learn how to
  • Interpret statistical jargon
  • Look for reproducibility, transparency, bias, and limitations
  • Convey information coherently to non-statisticians

Study power and sample size

• Review of p-value, significance level, effect size
• Formulas, software, and other resources for computing a sample size

Developing a Statistical Analysis Plan

• Using FDA guidance as a foundation, learn the steps and criteria needed to develop a statistical analysis plan (SAP).
• An SAP template will be given to all attendees.

Specialized topics/Closing Comments/Q&A

• Comparing Survival Curves
• Pharmacokinetics/Pharmacodynamics (PK/PD)
• Taking a holistic view to study design and interpretation
• Question and Answer session.

 

click to continue reading

Process Development and Validation rest on the right Design of Experiments and Statistical Process Control

The application of DOE and SPC to the development, design and monitoring of manufacturing and testing requires the use of procedures. Why? It is because in a recent guidance document on Process Validation, the FDA has named the Quality Unit as being responsible in the review and interpretation of DOE and SPC studies.

The Quality Unit needs to take a practical orientation when it sets out doing this work. An approach in which case studies and examples are sprinkled goes a long way in helping Process Validation professionals in their work. This is exactly what a seminar from GlobalCompliancePanel, a leading provider of professional trainings for the regulatory compliance areas, will offer and help regulatory professionals in the Quality Control and Quality Assurance areas achieve their aims.

The Director of this two-day seminar is Dr. Steven Kuwahara, who Founder and Principal, GXP BioTechnology LLC. Want to understand ways by which to adapt the right approach to applying DoE and SPC to the development, design and monitoring of manufacturing and testing? Then, please register for this very useful session by logging on to Process Development and Validation rest on the right Design of Experiments and Statistical Process Control . This seminar has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion.

Completely interactive

Dr. Kuwahara will do full justice to the role and importance of practical experiments in aiding an understanding of Design of Experiments. Theoretical information will be given only when it is needed to help gain an understanding of an experiment. At this highly interactive and practical session, Dr. Kuwahara will offer examples from real processes and testing procedures. He will intersperse these with examples that will be directly applicable to the areas of work that relate to the participants of this seminar.

An understanding of the way the process parameters relate to and work with each other is necessary for any pharmaceutical worker who is involved in performing, supervising or reviewing manufacturing or testing processes. The ability to monitor the performance of processes and test methods is also needed for such a worker. While this is true for a professional in any department of pharmaceuticals; it applies more to the worker who works in Quality Control and Quality Assurance, a requirement that has become necessary following the passage of recent FDA guidance document on Process Validation.

However, it is the development, manufacturing, or quality systems worker who carries out this work. In view of this fact, a high degree of coordination is needed between these two levels of employees. At this seminar, Dr. Kuwahara will arm these two levels of employees with the knowledge of the ways of designing the systems and studies, and then interpreting the results generated.

Dr. Kuwahara has charted out the following agenda for this seminar:

Dietary Design of Experiments

• Introduction
• One Level, One Factor Designs. Simple Comparisons
• Two-Level Multi-Factorial Design
• Extracting Information from the Experiment

Statistical Process Control

• Shewhart Charts for Variable Data
• Shewhart Charts for Attribute Data Especially Counts
• Considerations from Shewhart Charts
• Other Types of Charts Related to Shewhart Charts

This seminar is designed for the benefit of professionals involved in the procedures and applications of DOE and SPC, such as Directors, Managers, Supervisors, Lead workers in Process Development, Manufacturing, Regulatory Affairs, Quality Assurance and Quality Control, and workers who participate in operations or the are involved in the supervision of the development, manufacturing, or testing of medicinal products.

To join us for more information, get in touch

The use of Applied Statistics for FDA Process Validation

The use of Applied Statistics for FDA Process Validation is considered a matter of very high importance in the pharmaceutical industry. The FDA’s guidance for the industry, which it called “Process Validation: General Principles and Practices”, was set up in 2011. This guideline sets the framework for Process Validation in the pharmaceutical industry. The FDA prescribes a three-stage process that any organization in the pharmaceutical industry has to set up:

1. Process Design
2. Process Qualification

• Continued Process Verification.

The Process Design stage, which is called Stage 1, is when the organization defines the commercial manufacturing process. The knowledge that the organization has gained through development and scale-up activities serves as the basis for the development of this definition.

The Process Qualification, or Stage 2, involves evaluating the process design for the purpose of determining if the process defined in Stage I has the capability for reproducible commercial manufacturing.

The next stage of the FDA process validation stage is to determine if the Process Design stage and the Process Qualification stage give the ongoing assurance that the process remains in a state of control during routine production. This is what Stage 3, the Continued Process Verification, does.

Thorough understanding of how to implement Applied Statistics for FDA Process Validation

The ways of using Applied Statistics for FDA Process Validation will be the topic of a two-day seminar that GlobalCompliancePanel, a leading provider of professional trainings for the regulatory compliance areas, will be organizing. At this seminar, Richard Burdick, Emeritus Professor of Statistics, Arizona State University (ASU) and former Quality Engineering Director for Amgen, Inc., will be the Director.

Please visit http://www.globalcompliancepanel.com/control/globalseminars/~product_id=901132SEMINAR?wordpress-SEO to register for this meaningful and highly valuable seminar on applied statistics for process validation. This course has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion.

A methodical approach to implementing statistical methodologies

The focus of this two-day course on Applied Statistics for FDA Process Validation is the various ways by which a systematic approach to implementing statistical methodologies into a process validation program consistent with the FDA guidance can be established.

Dr. Burdick will begin with a primer on statistics, where he will explain how the methods of Applied Statistics for FDA Process Validation seminar can be applied in each remaining chapter.

The two fundamental requirements for Process Validation, namely the application of statistics for setting specifications and assessing measurement systems (assays), will be taken up next.

The next aspect of applied statistics Dr. Burdick will move on to is how to apply statistics through the three stages of process validation as defined by requirements in the process validation regulatory guidance documents.

Since the methods taught through all these three stages are recommended by regulatory guidance documents; this seminar on Applied Statistics for FDA Process Validation will provide references to the specific citations in the guidance documents.

The aim of this learning on Applied Statistics for FDA Process Validation is to lead participants into ways of establishing a systematic approach to implementing statistical methodologies into a process development and validation program that is consistent with the FDA guidance.

Complete learning on Applied Statistics for FDA Process Validation

Over the two days of this seminar, the participants will learn how to:

• Apply statistics for setting specifications
• Assess measurement systems (assays)
• Use Design of Experiments (DOE)
• Develop a control plan as part of a risk management strategy, and
• Ensure process control/capability.

All concepts at this Applied Statistics for FDA Process Validation seminar are taught within the three-stage product cycle framework defined by requirements in the process validation regulatory guidance documents.

Although aimed at the pharmaceutical industry, this seminar on Applied Statistics for FDA Process Validation provides a useful framework for other related industries, as well.

In this important learning on Applied Statistics for FDA Process Validation; Dr. Burdick will cover the following areas:

• Apply statistics to set specifications and validate measurement systems (assays)
• Develop appropriate sample plans based on confidence and power
• Implement suitable statistical methods into a process validation program for each of the three stages
• Stage 1, Process Design: utilize risk management tools to identify and prioritize potential critical process parameters; and define critical process parameters and operating spaces for the commercial manufacturing process using design of experiments (DOE)
• Stage 2, Process Qualification: assess scale effects while incorporating large (pilot and/or commercial) scale data; develop process performance qualification (PPQ) acceptance criteria by characterizing intra and inter-batch variability using process design data and batch homogeneity studies; and develop an appropriate sampling plan for PPQ
• Stage 3, Continued Process Verification: develop a control plan as part of a risk management strategy; collect and analyze product and process data; and ensure your process is in (statistical) control and capable.

keep enhancing FDA Process Validation

Data visualization can have a great effect on statistical presentations

It is said that a picture is worth a thousand words. This adage may appear figurative and allegorical when applied to the realm of statistics, but there is no denying the fact that a visual approach to statistics enlivens the subject like no other. A dash of pictorial work and some coloring at the right places enhance the presentation of otherwise drab statistical figures and slides dramatically.

Graphic displays illustrate the facts and truths behind statistics very artistically. They augment the appeal of what is conveyed by the statistical figures without altering or diluting the effect or the content. This is why presenting data visually is a great enhancer. It is very useful in any compliance analytics workflow.

Graphic enhancements can be used to uplift and raise the presentational aspects of statistics, but it requires skill and specific tools, because the pictorial aspect has to fit rightly into the statistical presentations. Any mismatch or mix-ups can have the opposite effect, making the statistical pictures gaudy, out of place and jarring.

Get to the ways of doing it

A two-day seminar from GlobalCompliancePanel, a highly respected provider of professional trainings for the regulatory areas, will offer thorough and complete learning on the proper ways of beautifying statistical presentations with the right mix of graphics, so that the intended purpose of embellishing is met.

James Wisnowski, who 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 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; will be the Director at this two-day seminar.

Please visit Data visualization can have a great effect on statistical presentations  to enroll for this highly interesting seminar, which has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion.

All about graphics in statistics

This seminar on data visualization will present methods using which participants can interactively discover relationships graphically. James will offer participants the foundations that will help them create better graphical information with which to accelerate the insight discovery process and improve the comprehension of reported results.

He will lead participants to an exploration of the 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. All this will be done using representative example data sets. Best practices for graphical excellence to most effectively, clearly, and efficiently communicate a thought will be explained. He will show how to 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 www.jmp.com), and open source solutions such as R (https://www.r-project.org) and Tableau Public (https://public.tableau.com/s/).

Meeting the requirements of analytic solutions

As all regulated industries have now come to expect data-driven decisions; compliance regulations require analytic solutions. The starting point of these solutions is the development of data visualization for discovering relationships and finish with crisp graphs communicating results. To take the example of 21 CFR and guidance documents for the pharmaceutical, biopharmaceutical, and medical device industries; these documents specify the application of statistical methods for the following:

• 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
• Determining process capability indices.

For each of these areas, data visualization serves as the foundation. Data visualization plays a major role in varying degrees in varied areas such as:

• meeting FDA analytical requirements for third-tier critical to quality attributes for analytical bio similarity evaluations where graphical plots and tables alone may sufficiently address compliance criteria

 

• HIPAA compliance, risk management and analysis, and many others of the quality functions.

James will show how to use data visualization and optimize the effect of these areas. The following agendas will be part of the two-day presentation:

• 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
• Human side of data visualization
• Principles of good graphic design
• Data visualization methodology
• Best practices
• Software introduction: JMP
• Univariate plots
• Distributions and histograms
• Pie graphs, violin plots, pareto plots, box plots
• Conditional formatting
• Mulitvariate plots and heatmaps
• Correlation
• Multivariate scatterplots and density graphs
• Contour plots
• Categorical data plots: treemaps, mosaic plots
• Software introduction: R
• Software introduction: Tableau Public
• Univariate plots with R and Tableau
• Multivariate plots with R and Tableau
• Dynamic and interactive graphs
• Brushing, dynamic linking, and filtering
• Profilers on response variables and optimization
• Time series plots
• Waterfall plots
• Sparklines and trend lines
• Statistical Process Control charts
• Maps
• Text data visualization
• Dashboards
• Course summary.