White Papers

• White Paper The Why and How of Asking Good QuestionsChristine Anderson-Cook discusses how and why asking good questions helps shape curiosity and makes you a better collaborator.
• White Paper Choosing the Right Design - with an Assist from JMP's Design ExplorerDeciding what data to collect for an experiment is a critical decision that has substantial consequences. In this paper, you'll learn how JMP's Design Explorer gives data scientists an easy way to construct and contrast multiple experimental designs that can be compared and evaluated.
• White Paper The Top 7 Myths That Lead to Really Bad GraphsIn this brief, we review seven of the most common misconceptions when visualizing data. When these myths are dispelled, your charts will be more effective and easier to design.
• White Paper Six Footprints for Leading Analytical ChangeIn this white paper, Tom Lange, retired Director of R&D at Procter & Gamble, passes on ideas, trends and best practices he's learned during a 40-plus year career building and leading analytical teams.
• White Paper JMP and Analytics in BaseballIn this white paper, Sig Mejdal, Assistant GM of the Baltimore Orioles, discusses the proliferation of quants in the sport and explores how JMP has helped bring analytics to baseball.
• White Paper Moving from Minitab to JMP: A Transition Guide, Version 2This guide explains how Minitab and JMP differ in the handling of descriptive statistics and visualizations. It is meant to ease the user’s transition from Minitab v19 to JMP 16 and JMP Pro 16. Focus is on the user interface, how tools are accessed, how analyses are performed, and the general workflow of the packages.
• White Paper Moving from SPSS to JMP: A Transition GuideThis guide explains how SPSS and JMP differ in the handling of descriptive statistics and visualizations. It is meant to ease the user’s transition from SPSS Version 27 to JMP 16 and JMP Pro 16.
• White Paper JMP takes the struggle out of data wranglingThis paper provides an introduction to the unglamorous, time-consuming, laborious, and sometimes dreaded “dirty work” of statistical investigations – data preparation. The good news: JMP can perform these operations with ease.
• White Paper Measurement Systems Analysis for Curve DataJMP Pro does an impressive job quickly and simply solving Measurement Systems Analysis with curve data, a complex and relevant problem.
• White Paper JMP Synergies: Using JMP and JMP Pro With Python and R There may be occasions where you'll want (or need) to use JMP in conjunction with open source tools. This paper will help you to get started using the Python and R connections in JMP.
• White Paper The JMP Design of Experiments AdvantageThis paper details the state-of-the-art DOE capabilities offered by JMP to help you tailor designs to your specific problem and resource limitations.
• White Paper The Integration of Big Data Analytics into a More Holistic ApproachThis paper explores the fundamentals of big data analysis, showing how big data applications can be better integrated to achieve a more streamlined, holistic outcome.
• White Paper Improving Processes with Statistical ModelsHow, when and where do I apply statistical modeling to a problem? Find out in these two real-world case studies.
• White Paper Optimizing Processes with Design of ExperimentsWhat is design of experiments (DOE), and how does it deliver value? Through a case study approach, this white paper answers these questions and more.
• White Paper Optimizing Pharmaceutical Production Processes Using Quality by Design MethodsGood news! Did you know that your quality by design goals can be derived in a straightforward way, the results can be easy to verify and that this method allows for further improvement of the processes without the need for re-registration? Find out more with this case study from pharma.
• White Paper Effective Visualization Techniques for Data Discovery and AnalysisHow do you communicate highly technical data to a non-analytical audience? Find out how in this paper on best practices in data visualization.
• White Paper Tap Into Unstructured DataThis white paper discusses ways to explore, analyze and use insights from unstructured text data.
• White Paper Split-Plot Designs: What, Why, and HowLearn how to design and analyze split-plot experiments and why split-plot designs are often cheaper and more efficient than other methods.
• White Paper Evaluating the Measurement Process: A Better Way to Do Repeatability & Reproducibility StudiesStatistician, author and quality expert Donald J. Wheeler, explains data collection strategy in the context of a basic EMP and gage R&D study.
• White Paper Moving From Minitab to JMP: A Transition GuideA practitioner's review of JMP vs. Minitab: unearth two different approaches to common statistical techniques and principles.
• White Paper Smart Machine Learning for ManufacturersThis paper introduces the 'smart machine learning' framework which unites the need to understand both the unique aspects of the data that is collected and the perspective of the data scientists who oversee its collection.
• White Paper Big Data, Pharma 4.0 and Process ModelingHow can you prepare for Industry 4.0? This paper outlines how to improve process knowledge, close the gaps for legacy products and set the foundation for big data use.
• White Paper Definitive Screening Designs with Added Two-Level Categorical FactorsInventors of Definitive Screening designs share a new development in this reprint from the Journal of Quality Technology.
• White Paper Class of Three-Level Designs for Definitive Screening in the Presence of Second-Order EffectsIntroducing….a class of economical three-level designs for screening quantitative factors.
• White Paper Advantages of Bootstrap Forest for Yield AnalysisMaintain a high level of quality and control (in less time) with the bootstrap forest method. Here’s how!
• White Paper Explaining Reliability GrowthLearn about statistical techniques used to improve product and process reliability over time, and see specific examples using JMP software.
• White Paper Data Exploration in Preparation for ModelingCase study: uncover the process a leading catalog retailer uses to prep data before building response models.
• White Paper Visualizing Change: An Innovation in Time-Series AnalysisData in motion: how good interactive graphs illustrate the shape, velocity and direction of change.
• White Paper How R&D Labs Can Learn More From Their Positive ControlsThe ultimate goal is to build models that predict a future that can be precisely reproduced by anyone,at any time So, how can two people get different results despite using the same equipment and protocols? Find out.
• White Paper Statistical Intervals: Confidence, Prediction, EnclosureThis paper uses a manufacturing example to describe the differences between confidence, prediction and tolerance intervals.
• White Paper Visual Six Sigma: Making Data Analysis LeanThis paper introduces the idea of "Visual Six Sigma," a practical, pragmatic and yes, visual approach to data analysis and process improvement.
• White Paper Risk-Based Monitoring of Clinical Trials Using JMP ClinicalClinicians discover a better way to protect the well-being of patients by reviewing trial data remotely.