White Papers und Kapitel

• Bootstrap-Forests für die Halbleiter-Ergebnisanalyse in JMPHalten Sie ein hohes Maß an Qualität und Kontroll (in kürzerer Zeit) mit der Bootstrap-Forest Methode. Sehen Sie hier wie!
• Bootstrapping – ein neuer Standard in Anwendung und Lehre? Mit Bootstrapping Können Sie Verteilungsinformationen aus Datensätze gewinnen.
• Der Random Forest als ein robustes Verfahren zum Screening wichtiger FaktorenLernen Sie über Random Forest, ein Klassifikationsverfahren, welches aus mehreren, unkorrelierten Entscheidungsbäumen besteht.
• Die Vorteile der JMP® VersuchsplanungDieses White Papier beschreibt die neuen JMP DOE-Funktionen, die Ihnen helfen, Maßgeschneiderte Designs auf Ihr spezifisches Problem und Ressourcenbeschränkungen anzupassen.
• Elastic Net und Lasso: Lassen Sie in unübersichtlichen Situationen Software statistische Modelle findenIn diesem White Paper werden LASSO und Elastic Net Verfahren zur Bildung linearer Modelle beschrieben, um robuste und zuverlässige Modelle zu erstellen.
• Erste Schritte in die digitale ZukunftIn diesem Artikel beschreibt Bernd Heinen, was es mit der digitalen Revolution auf sich hat und wie man Herr seiner Daten wird.
• Implementing CDISC Using SAS: An End-to-End Guide, zweite AusgabeMit diesem kostenlosen Buchkapitel lernen Sie die Vorteile der Auswertung von CDISC-Daten mithilfe von JMP Clinical
• Information Quality: The Potential of Data and Analytics to Generate Knowledge.InfoQ ist eine Denkweise, die unseren Ansatz zur Datenanalyse lenkt und hilft, Datenmissbrauch zu verhindern. Dieses Kapitel enthält zwei Beispiele dafür, wie JMP InfoQ unterstützt.
• Optimierte Prozesse dank VersuchsplanungWas ist Versuchsplanung (DOE) und warum ist es Wert? Durch einen Fallstudienansatz beantwortet dieses Whire Paper diese Fragen und mehr.
• Partielle kleinste Quadrate mit JMP kennen lernenSehen Sie, wie Partielle kleinste Quadrate (PLS) verwendet wird, um ein Medikament Entwicklungsdilemma zu lösen. Dabei werden die Beziehungen zwischen Eingabedaten und Ergebnissen auch bei korrelierten und ungenauen Eingabedaten modelliert.
• Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SAS – eine EinführungAutor Richard Zink schlägt vor, den Ablauf klinischer Studien durch das Beseitigen manueller, papierbasierter Datenprüfungsmethoden zu revolutionieren.
• Verbesserte Prozesse dank statistischer ModelleWie wann und wo wenden Sie statistische Modellen an ein Problem an? Finden Sie heraus, in diesen praxisorientierten Fallstudien.
• Visual Six Sigma mit JMPErfahren Sie über die Gründe für die Verwendung von Visual Six Sigma und die zugrundeliegenden Strategien und Verfahren.

• Analyzing and Interpreting Continuous Data Using JMPDownload a complimentary chapter from Analyzing and Interpreting Continuous Data Using JMP by Brenda Ramirez and Jose Ramirez.
• Building Better Models with JMP ProDiscover the “what, why and how” of neural networks through case studies, figures and exercises. Examples demonstrate how models are used for both classification and prediction across an array of applications.
• 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.
• Classification of Breast Cancer Cells Using JMPSee how the Wisconsin Breast Cancer Diagnostic Data Set is being used to classify malignant and benign tumors.
• Component Integrated Importance: Modeling Complex Aging SystemsLearn about the two alternative methods that are better suited to evaluate aging systems.
• Data Mining Techniques, Third EditionData Miners, Inc. co-founders explain how to create derived variables through a study on modeling customer attrition.
• 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.
• Detecting Fraud at the Clinical SiteOrganizations find a better way to protect participants in clinical trials. Learn the graphical and statistical approaches being used to identify site- and patient-perpetrated fraud.
• Disproportionality Analysis and Its Application to Spontaneously Reported Adverse Events in PharmacovigilanceHow do you define an adverse event incidence for a particular drug when there is no clear denominator? Find out how with this whitepaper.
• 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.
• Efficient Modeling & Simulation of Biological Warfare Using Innovative Design of Experiments MethodsSee how proven DOE methods can be used to model complex scenarios involving many variables – such as biological warfare attacks.
• Evaluating the Measurement Process: A Better Way to Do Reliability & 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.
• Generating Adverse Event Narratives Using JMP ClinicalNew analytical process available to streamline the time-consuming task of creating patient narratives. Learn more about this function in JMP Clinical.
• Import and Analysis of Summarized Data from Sequencing Studies with JMP Genomics 5.1Analyze, visualize and discover hidden patterns within variant and count data. Learn how JMP Genomics provides tertiary statistical analysis for data generated from high-throughput sequencing studies.
• Information Quality: The Potential of Data and Analytics to Generate Knowledge.New case studies: find out how Information Quality was used as a guide to predict water quality and control a film deposition process.
• Lean Data Analysis: Simplifying the Analysis and Presentation of Data for Manufacturing Process ImprovementPredict, analyze, improve and control the quality of your product with helpful tips in this article on data analysis maturity models.
• 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.
• Moving from SPSS to JMP: A Transition GuideSPSS vs. JMP: What are the key differences between these two data analysis tools?
• NumbersenseDo you want to better target your marketing offers to potential customers using predictive modeling? Statistician Kaiser Fung explains his definition of successful targeting and the law of diminishing returns.
• Optimal Design of Experiments: A Case Study ApproachWhat is a blocked experiment? When is one used and how is it constructed? Find out in this case study.
• 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.
• Predictive Analytics for the Eyes and MindWhat makes for great data visualization? Find out from expert Stephen Few, IT Innovator, Author and Prinicipal of Perceptual Edge.
• Predictive Analytics Via Text MiningDownload a complimentary chapter about text mining for predictive analytics.
• Problem Solving for New Engineers: What Every Engineering Manager Wants You to KnowDownload a complimentary chapter about the strategy and tools needed to solve problems through experimentation.
• Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SASCreate a centralized view of trial data to alert you to quality and safety issues with this introductory guide.
• 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.
• SPC Data Visualization of Seasonal and Financial Data Using JMPVoila: how to access your Shewhart, CUSUM and moving average charts with a simple drag and drop interface.
• 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.
• Spreadsheets: Friend or Foe? A Best Practice Approach for Conducting Your What-if AnalysesThis paper highlights the inherent risks and compromises in using a spreadsheet tool like Excel to analyze data. There’s a better way!
• Statistical Intervals: Confidence, Prediction, EnclosureThis paper uses a manufacturing example to describe the differences between confidence, prediction and tolerance intervals.
• Statistics with JMP: Graphs, Descriptive Statistics and ProbabilityNeed a better understanding of basic statistical theory and its applications? Let Professors Peter Goos and David Meintrup be your guide! An overview of descriptive statistics for nominal, ordinal and quantitative data, with particular attention to graphical representations is provided.
• Statistics with JMP: Hypothesis Tests, ANOVA and RegressionAnother great instruction guide by Professors Peter Goos and David Meintrup! This chapter specifically covers discrete and continuous random variables, with a focus on bivariate probability distributions and densities.
• Survey Data Analysis: The FundamentalsNew case study demonstrates best practices for survey analysis in JMP (including tips for dealing with missing data).
• Tap Into Unstructured DataThis white paper discusses ways to explore, analyze and use insights from unstructured text data.
• The Improbability PrincipleDownload a complimentary chapter from David Hand's well-known book, The Improbability Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day.
• The State of Market ResearchWhat are the top two tools market researchers need to turn data into information through analysis? Find out in this chapter that outlines the state of market research.