On-Demand Webinars
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A Case for Sophisticated Data Analytics in Process-Enabling Industries -
Biotronik: Accelerate Product and Process Development with Design of Experiments (DOE) -
Accelerated Destructive Degradation Analysis -
Accelerated Life Testing -
Accelerating R&D for the Autonomous and Electric Vehicles Industry -
Accessible Analytics for Marketing -
Accessible, Intuitive Statistics for Scientists and Engineers -
Addressing the Challenges of Data Variety -
Advanced Decision Trees -
Advantages of Bootstrap Forest for Yield Analysis: A Semiconductor Case Study -
Adverse Event Signal Detection Using Bayesian Hierarchical Modeling -
Analytical Method Development -
Analytical Thinking and Problem Solving: The Mindset for Success -
Analytics Lessons From Baseball -
Anatune: Data analytics for analytical method development -
Applications of Modern Design of Experiments (DoE) -
Applied Statistics From the Classroom to the Boardroom -
Applying Quality Engineering Principles to Create Innovative Products -
AstraZeneca: Future chemistry: exploring the possibility space
B
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BACKUP - Bridging Statistics and Chemical Engineering for Biotech and Pharma -
Basic Navigation: Part 1 -
Basic Navigation: Part 2 -
Basic Statistics and Analysis -
Bayesian Inference in Reliability -
Become an Analytics Advocate at Your Organization -
Best Practices for Building Quick and Useful Dashboards -
Best Practices in Data Visualization -
Beyond Dashboards: Designing Dashboards That Users Actually Like -
Beyond Spreadsheets Part 2: Graph Builder: The Two Laws of Analytics -
Bill Meeker and Chris Gotwalt: Improving Product Reliability -
Boosting Performance With Custom Designed Experiments -
Bridging Statistics and Chemical Engineering for Biotech and Pharma -
Bringing Science to the Masses -
Build - and Choose - Better Models Faster: Data Scientists in a Box
D
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Dashboard Building with JMP -
Data Access and the Future of Statistics -
Decision Trees -
Delivering Value With a New Generation of Reliability Analysis and Survival Estimation Methods -
Design experiments to be robust to input variation -
Design of Experiments for BioTech/Pharma Manufacturing -
Design of Experiments in Lean Product Development -
Design of Experiments With Mixtures: A Case Study in Plastics Formulations -
DOE Case Studies -
Don’t Waste Good Analysis on the Wrong Problem -
Doug Montgomery: Optimizing Results With Data-Driven Experimental Design -
Dr Reddy’s: How to make analytical methods fit-for-purpose
E
F
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Gene Expression Analysis for Absolute Beginners -
Generating Insights from Data -
Getting Started with Design of Experiments: When Many Factors Matter -
Glean and Visualize Deeper Insight from Your Data -
Going Beyond Spreadsheet Analytics With Visual Data Discovery -
Going Beyond Spreadsheets -
GSK: Optimising your experimentation process using JMP
H
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Hear From Design of Experiments Thought Leaders -
Helping Domain Experts Understand Their Data -
Helping Students Understand the Power of Statistics -
How Do You Build a Great Analytic Culture? -
How Industrial Statistics Has (and Hasn’t) Changed -
How P&G Saved Millions and Improved Quality With Analytics -
How to Add Structure to Your Decision Making -
How to Be a Data Datective -
How to Design for Robust Production Processes -
How to ensure your investment in Machine Learning yields beneficial outcomes -
How to Gain Insights With Text Exploration -
How to Model Complex, High-Dimensional Chemical Spectra -
How to Model Complex, High-Dimensional Chemical Spectra -
How to Reduce Costs Through Visual Analysis -
How to Save Time With Repeatable Analyses -
How to Succeed in Data Mining and Predictive Analytics
I
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Identifying Drug-Induced Liver Injury -
Improving Existing Processes -
Improving Mining Operations With Statistics -
Improving Product Reliability With Quality By Design -
Improving Your Process With Statistical Models -
Innovation in the Chemical Industry With Statistics and DOE -
Interactive and Semi-Automated Reporting on the Safety and Efficacy of Clinical Studies - DIA -
Introducing JMP Live -
Introduction to Modeling and Model Comparison
J
M
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Make Statistical Thinking Your Strategy for Solving Problems -
Make Your Experiments Count: DOE Expert Bradley Jones -
Marketing in a Digital Age: The Democratisation of Analytics -
Meta-Analysis of Genomics Data -
Mission-Oriented Analytics: New Methods for the Intelligence Community -
Model Selection for Designed Experiments -
Modern Clinical Monitoring And Quality By Design -
Modernization Updates in JMP Clinical -
Monitor, Understand and Optimize Your Processes: A Manufacturing Case Study -
Moving from SPSS to JMP -
Multiple Testing Correction: Why, When and How
O
P
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Pharmaceutical Method Transfer -
Pharmaceutical Product Stability -
Predicting Product Reliability: A Case Study -
Predictive Analytics For Smarter Business Decision Making -
Predictive Analytics Theory for Real Business Problems -
Predictive Modeling for Risk of Disease -
Predictive Modeling in the Life Sciences -
Predictive Modelling - From Naive Bayes to Deep Learning -
Preparing Students to Be Successful Data Analysts -
Probability Plots in Life Distribution -
Producers, Consumers, and Servicers: Three Perspectives on Reliability -
Prolific Author on Split-Plot and Optimal DOE Shares Insights
Q
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Screening and Controlling Manufacturing Processes for Faster Process Improvement -
Sentiment Analysis: What Are People Feeling? -
Session 1: Accessing Data | Beyond Spreadsheets Part 1: Breaking Away from Spreadsheets -
Session 2: Data Preparation | Beyond Spreadsheets Part 1: Breaking Away from Spreadsheets -
Session 3: Data Visualization | Beyond Spreadsheets Part 1: Breaking Away from Spreadsheets -
Session 4: Basic Analysis and Modeling | Beyond Spreadsheets Part 1: Breaking Away from Spreadsheets -
Session 5: Sharing Results | Beyond Spreadsheets Part 1: Breaking Away from Spreadsheets -
Solutions to Data Preparation Challenges -
Solvay: Industrial data science for chemical process perfection -
Stan Higgins, OBE: Capturing value from your data to accelerate innovation -
Start being predictable: improve your experimentation -
State of the Art Strategies for Clinical Trial Monitoring -
Statistical Discovery in Quality Engineering -
Statistical Engineering: A Holistic Problem-Solving Approach -
Statistical Exploration for Research & Development -
Stepwise Regression -
Symrise: Mastering complex processes with Design of Experiments
T
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Tackling Unstructured Data With Text Exploration -
Imperial College: Teaching Design of Experiments to chemists: lessons from Imperial College London -
The Applied Statistics Gap -
The Elements of Sophisticated Reliability Analysis -
The Judgment Calls We Make in Dashboard Design -
The Key to Good Graphs -
The Power of Crowdsourcing Data Science Ideas -
The Science of Luck -
To Explain or Predict? That Is the Question -
Traditional and New Quality Techniques for Process Improvement -
Triskaidekaphilia: Introducing JMP 13
U
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Understanding Customer Needs With Choice Modeling -
Unlocking the Value of Text Analytics -
Use Data Exploration for a Competitive Advantage -
Using Bayesian Methods in Business and Marketing -
Using Data to Align With Your Life Purpose -
Using Design of Experiments To Increase Predictability, Optimise Processes and Minimise Costs -
Using Experimental Design to Increase Predictability, Optimize Processes and Lower Costs -
Using Predictive Analytics to Spot Patterns and Uncover Solutions -
Using Reliability Block Diagrams in System Design -
Using Statistical Process Controls to Improve and Monitor Your Process
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W.L. Gore: Using Statistics as a Competitive Advantage -
Want to Innovate? The One Question You Must Ask -
Want to Make More Effective Graphs? -
What Does It Take to Be a Successful Statistician? -
What Does It Take to Effect Change With Analytics? -
What Every Engineering Manager Wants You to Know -
What It Takes to Be an Effective Industrial Statistician -
Why Customer Satisfaction Is Not Enough -
Why Don’t More Businesses Experiment? -
Why Rare Events Happen Every Day -
Why We All Need Data Science Skills -
Worst Practices in Data Mining