On-Demand Webinars
A
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A Case for Sophisticated Data Analytics in Process-Enabling Industries -
Accelerated Destructive Degradation Analysis -
Accelerated Life Test Planning -
Accelerated Life Testing -
Accelerating Innovation Through Faster Process Development -
Accessible Analytics for Marketing -
Accessible, Intuitive Statistics for Scientists and Engineers -
Accessing Databases -
Addressing the Challenges of Data Variety -
Advanced Decision Trees -
Advanced Techniques for Working with Big Data -
Advantages of Bootstrap Forest for Yield Analysis: A Semiconductor Case Study -
Adverse Event Signal Detection Using Bayesian Hierarchical Modeling -
Analysing and Improving Quality and Reliability -
Analysis of Recurrence Data -
Analytical Method Development -
Analytical Thinking and Problem Solving: The Mindset for Success -
Analytics Lessons From Baseball -
Analyzing Genetic Diversity and Applying Genomic Selection Methods for Plant Breeding -
Analyzing Reliability for Non-Repairable Systems -
Analyzing Reliability for Repairable Systems -
Analyzing Survival Data -
Applied Statistics From the Classroom to the Boardroom -
Applying Quality Engineering Principles to Create Innovative Products -
Automating Analyses Using JMP Scripts
B
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Basic Analysis and Plotting -
Basic Navigation: Part 1 -
Basic Navigation: Part 2 -
Basic Statistics and Analysis -
Basics for Using Graph Builder -
Bayesian Inference in Reliability -
Become an Analytics Advocate at Your Organization -
Best Practices for Automating the Creation of Adverse Event Narratives -
Best Practices for Building Quick and Useful Dashboards -
Best Practices in Data Visualization -
Beyond Dashboards: Designing Dashboards That Users Actually Like -
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 -
Building Better Predictive Models Using JMP Pro® -
Building Custom Applications Using JMP®
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Building Dashboards to Access and Share Updated Analyses -
Building Linear Mixed Models Using JMP Pro -
Building Predictive Models for Spectral Data
C
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Cleaning and Preparing Complicated Data -
Clinical Trial Safety Analysis With JMP Clinical -
Collaborating Using JMP® Live -
Creating Custom Drill-Down Graphs to Enhance Interactive Reporting -
Creating JSL Libraries of User-Defined Functions -
Creating Summary Tables using Tabulate -
Creating, Using and Sharing JMP Journals
D
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Dashboard Building with JMP -
Data Access and the Future of Statistics -
Data Analytics Adds Value in the Mining Industry -
Data Mining and Predictive Modeling -
Decision Trees -
Defective Subpopulation Distributions -
Degradation Analysis -
Deriving Sentiments from Opinions or Product Choices -
Design Diagnostics -
Design of Experiments in Lean Product Development -
Design of Experiments With Mixtures: A Case Study in Plastics Formulations -
Designing Experiments to Optimize Manufacturing Materials Selection -
Designing Mixture Experiments - Part 1 -
Designing Mixture Experiments - Part 2 -
Discovering and Predicting Patterns Using Neural Network Models -
DOE Case Studies -
Don’t Waste Good Analysis on the Wrong Problem
E
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Essentials of Designing Experiments Using JMP® -
Estimating the Degradation Rate of Photovoltaic Arrays Using a Two-Component Nonlinear Model -
Evaluating & Monitoring Your Process Using MSA and SPC -
Exploratory Data Analysis and Dynamic Graphs -
Exploring Capability Analysis -
Exploring Customer Behavior With Market Research Models and Survey Analysis -
Exploring Customer Perceptions with Maximum Difference Scaling -
Exploring your Data Using Interactive Graphs
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Exploring Your Data With Custom Mapping -
Expression/NextGen Sequencing Analysis for Translational Genomics -
Extracting Practical Information from Quality-by-Design Models
F
G
H
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Handling Constraints When Designing Experiments -
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 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 Gain Insights With Text Exploration -
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 -
Identifying Important Variables in Your Data -
Identifying Unusual Patterns that Might Indicate Data Integrity Issues -
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 -
Introducing JMP Live -
Introduction to Modeling and Model Comparison
J
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JMP 15 is here -
JMP Clinical: Centralized Statistical Monitoring of Clinical Trials -
JMP Clinical: Generating Semi-Automated Patient Narratives for Regulatory Submission -
JMP Pro for Academic Research -
JMP Scripting Language for Experienced JSL Users – Part 1 -
JMP Scripting Language for Experienced JSL Users – Part 2 -
JMP® and R Integration -
JMP® Clinical: Conducting Medical Safety Reviews of Clinical Trials -
JSL for Building Interactive Dialogs for Automating Workflows
M
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Machine Learning and Biomarker Sub-Group Analysis for Precision Medicine -
Make Statistical Thinking Your Strategy for Solving Problems -
Make Your Experiments Count: DOE Expert Bradley Jones -
Meta-Analysis of Genomics Data -
Mission-Oriented Analytics: New Methods for the Intelligence Community -
Model Selection for Designed Experiments -
Modern Genomic Methods for Crop Improvement in Breeding Programs -
Modernization Updates in JMP Clinical -
Monitoring and Controlling Complex Manufacturing Processes -
Monitoring, Diagnosing and Improving Large-Scale Complex Processes -
Moving from SPSS to JMP -
Multiple Testing Correction: Why, When and How
N
O
P
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Pharmaceutical Method Transfer -
Pharmaceutical Product Stability -
Pinpointing and Reducing Defects -
Predicting Product Reliability: A Case Study -
Predictive Analytics Theory for Real Business Problems -
Predictive Modeling for Risk of Disease -
Predictive Modeling in the Life Sciences -
Preparing Students to Be Successful Data Analysts -
Preparing Your Data for Analysis -
Probability Plots in Life Distribution -
Producing and Interpreting Basic Statistics Using JMP® -
Prolific Author on Split-Plot and Optimal DOE Shares Insights
Q
R
S
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Screening and Controlling Manufacturing Processes -
Screening and Controlling Manufacturing Processes for Faster Process Improvement -
Sharing Your Results -
Single-Cell RNA-Seq Analysis -
Solutions to Data Preparation Challenges -
Specialized Custom DOE for Experienced Experimenters -
Specialized Modeling Techniques for Interpreting Consumer Studies -
Specifying and Fitting Models -
Split-Plot and Strip-Plot Design of Experiments -
State of the Art Strategies for Clinical Trial Monitoring -
Statistical Engineering: A Holistic Problem-Solving Approach -
Stepwise Regression
T
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Tackling Unstructured Data With Text Exploration -
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 -
Time Series Analysis and Forecasting -
Time Series Forecasting -
To Explain or Predict? That Is the Question -
Toward a More Effective Disease Outbreak Alert System: A Symptoms Approach to Biosurveillance -
Tracking and Trending Manufacturing Metrics -
Traditional and New Quality Techniques for Process Improvement -
Transforming Data to Make Better Predictions -
Triskaidekaphilia: Introducing JMP 13
U
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Uncover the Key Data Necessary to Reduce Your Hidden Factory -
Understanding and Applying Tree-based Methods for Predictor Screening and Modeling -
Understanding Customer Needs With Choice Modeling -
Understanding DOE Capabilities in JMP® -
Understanding the Principles for Building Predictive Models -
Unlocking the Power of Graph Builder -
Unlocking the Value of Text Analytics -
Use Data Exploration for a Competitive Advantage -
Using Bayesian Methods in Business and Marketing -
Using Blocking When Designing Experiments -
Using Data to Align With Your Life Purpose -
Using Definitive Screening Designs to Get More Information from Fewer Trials -
Using Experimental Design to Increase Predictability, Optimize Processes and Lower Costs -
Using Formulas to Get the Most from Your Data -
Using Generalized Regression in JMP Pro to Create Robust Linear Models -
Using Geographic Maps -
Using JMP® for Marketing Analytics and Consumer Research -
Using JMP® Pro for Enhanced Marketing Analytics and Consumer Research -
Using JMP® Pro to Build Models Using Generalized Regression Variable Selection Techniques -
Using JMP® Pro to Model Functional Data -
Using JMP® to Harness the Full Power of SAS -
Using Multivariate Methods to Explore Data -
Using Partial Least Squares - When Ordinary Least Squares Regression Just Won’t Work -
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 -
Using Structural Equation Models to Uncover Relationships between Observed and Latent Variables -
Using Text Explorer to Extend Analysis
V
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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? -
Well Performance Evaluation With Data-Driven Analytics to Optimize a Hydraulic Fracture Strategy -
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 the Future of Manufacturing Depends on Statistical Data Analysis -
Why We All Need Data Science Skills -
Working With and Interpreting COVID-19 Data -
Worst Practices in Data Mining