Click here to register JMP Student Edition has a range of capabilities suitable for teaching statistics in psychology, sociology, economics, and other social science disciplines. This webinar provides a survey of these capabilities and how each is implemented in an interactive, point-and-click interface. If you don’t yet teach with JMP Student Edition, this webinar will help you decide if it’s rig...
Click here to register Nonlinear modeling, while not taught as frequently as linear modeling, is a critical technique for students to learn across many science and engineering disciplines. JMP Student Edition offers easy-to-use nonlinear modeling tools for fitting both standard and custom models. This webinar shows you how to use these nonlinear modeling tools effectively with your students. Topic...
Click here to register JMP software is used extensively by the world’s major pharmaceutical companies for statistical analysis in R&D, quality by design (QbD), manufacturing, and clinical trial analysis. This makes JMP Student Edition a natural choice to teach statistical methods in pharmaceutical sciences. This webinar provides a survey of relevant JMP capabilities, so that if you’re considering ...
売上、在庫量、センサーの測定値など、企業で扱うデータの多くは、時間とともに記録される「時系列データ」です。こうしたデータを扱う場面は、近年ますます増えています。 本セミナーでは、実在の時系列データを題材に、時系列データの可視化から、回帰による要因の定量化、時系列モデルによる予測とWhat-if分析までを、デモを交えて解説します。 回帰では前後の値が関係し合う点（自己相関）に注意が必要ですが、その特性を活かした時系列モデルを使えば的確な予測が可能です。JMPならではの扱い方のコツと、業務データを予測や意思決定に活かすヒントが得られます。 詳細・お申込み JMPではじめる時系列データ分析 ～業務データを可視化・分析・予測する～ | JMP
Video using JMP 19 was posted in August 2026. When data do not follow a straight line, understanding complex, nonlinear relationships is key to uncovering deeper insights. See how to fit, visualize, and interpret nonlinear patterns using JMP’s modeling and visualization tools. Learn how to quickly visualize nonlinear trends, apply the Fit Curve platform for flexible curve fitting, and deploy nonl...
Ordinary least squares regression is a foundational statistical method in many academic research settings, but to draw meaningful conclusions from the results, you first should confirm that the regression model doesn’t exhibit any problems. If you’re in need of a primer on common problems in regression modeling and what to do if you encounter them, then this JMP Academic webinar is for you. Top...
スペクトルデータやクロマトグラムデータは、多数の波長や時点における強度などを測定するという意味において、典型的な多変量データと言えます。これらのデータは多変量の解析方法に従って解析することで、データの分類やモデル化が可能になります。本セミナーでは、JMP製品（JMP、JMP Pro）を用いて、この種のデータに対して多変量解析を実施する方法とそのメリットを解説します。 ※本セミナーは、セミナー時点での最新バージョン「JMP（JMP Pro） 19.1.3」を用いています。バージョンアップによって、レポートや操作方法等が変更される可能性があります。 （目次) イントロダクションと可視化PCA（主成分分析）とPLS回帰「関数データエクスプローラ」を使った関数主成分分析解析例：配合成分比とスペクトルの形状との関連性 1. イントロダクションと可視化（14分25秒） データ解析におけるスペク...
2026年5月28日に実施したベイズ最適化セミナーのオンデマンド版です。
セミナーの録画内容を編集し、セミナー内容を5つのパートに分けています。
※本セミナーは、セミナー時点での最新バージョン「JMP Pro 19.1.2」を用いています。バージョンアップによって、レポートや操作方法等が変更される可能性があります。
JMP Proのベイズ最適化について
（目次）
1. 最適化していくイメージ
2. Bayes最適化の基本概念
3. 実験計画法（DOE）を用いた最適化とBayes最適化との対比
3-1. DOEによる最適化
3-2 Bayes最適化による最適化
4. JMP Pro 「Bayes最適化」プラットフォームの特徴
5. Bayes最適化の実践例
5-1 事例1:酵素触媒反応の収率最適化
5-2 事例2:プラスチック射出成形の最適化
イントロダクション（8分19秒）
(view in ...
JMP Student Edition 19 is available now and is packed with exciting new features. This webinar reviews a selection of new features relevant to instructors and researchers, from interface improvements to entirely new analysis platforms, including: Data table enhancementsGraph Builder improvementsJMP Notebook interface for coding with JSL and PythonBayesian optimizationPropensity score methods fo...
Teaching time series analysis and forecasting involves establishing foundational concepts, such as stationarity and autocorrelation, as well as teaching one or more specific analysis techniques. JMP Student Edition’s interactive time series tools can help you make these concepts and techniques more approachable to students. This webinar guides you in using JMP Student Edition to teach time seri...
Video using JMP Pro 19 was posted in November 2025. This session is for R&D product and process engineers responsible for innovating quickly to be the first to market with a new product. Bayesian optimization is an iterative learning technique that uses a model to generate new candidate runs for assessment. Bayesian optimization learns from the responses with each iteration and gives us clearer gu...
After mastering simple and multiple regression, students can build skills in advanced regression techniques for situations that standard least squares can't readily handle. This webinar, intended for statistics instructors, guides you in using JMP Student Edition to teach a selection of advanced regression techniques for performing model selection, avoiding overfitting, and handling non-normal ...
Video using JMP 19 was posted in October 2025. Bayesian Optimization accelerates industrial R&D and lowers the barrier to entry. It saves time and resources by learning from observed response values while using the project goals to recommend the settings to test next. See how to use JMP Pro Bayesian optimization tools to go beyond the limitations of traditional DOE, where augmentation is based ...
Video using JMP Pro 18 was posted in October 2025. Do you face challenges with restrictive data formats from EDS, XRD, or Raman instruments? Are the exported spectra and reports too static, offering little flexibility for customization or deeper analysis? Do you need tools that allow flexible peak detection, baseline correction, background subtraction, and high-quality figure generation for peer ...
Video using JMP Pro 18 was posted in September 2025. Do you need to simulate the results of your model to help determine how to measure and reduce defect rates? Do you aim to compare the impact of changing variable values on one or more response goals, such as cost and yield? Could your team find value in understanding the impact of factor limits on the expected defect rate of future runs and the...
Structural equation modeling (SEM) is a general-purpose modeling framework that is useful for testing theories about complex interrelationships between variables, both observed and latent. For example, SEM could be applied to employee survey data to test competing theories about how motivation, stress, leadership, compensation, and job satisfaction influence one another. While traditionally ap...
In analyzing data from quantitative studies, researchers often run into a common statistical challenge: The observations aren’t independent from one another. For example, if an ecology study is conducted across multiple geographic locations, observations may not be independent due to uncontrolled environmental factors that differed across locations. Or if a survey study involves repeatedly sur...
If there’s one caveat that most of us remember about least squares regression, it’s this: Regression assumes normality. More specifically, least squares regression assumes that the distribution of Y given X is normal, or equivalently, that the distribution of residuals is normal. But what if our data violate this assumption (e.g., our response distribution is highly skewed or consists of only ...
With the JMP Student Edition, academic researchers get no-cost access to all JMP Pro capabilities, such as Python integration and more advanced tools for building machine learning models. This webinar will demonstrate advanced analytical applications for researchers in Chemistry, Chemical Engineering, Materials Science, and related fields by enhancing JMP Student Edition’s native features with...
In biostatistics, survival analysis is a collection of statistical methods for analyzing the time it takes for some event of interest to occur (i.e., time-to-event data). For example, a study of disease progression might assess time to patient mortality or recovery. Survival analysis helps researchers understand how the probability of a biological or medical event changes over time and how that...
Which Model When? The models you use depend on your data, the questions you are trying to answer and the problems you want to solve. See how to decide by working through case studies that illustrate how to identify, fit and evaluate models that might be most useful in achieving your analysis goal. (view in My Videos)
Die verwendeten Modelle sind abhängig von Ihren Daten, den Fragen, die Sie beantworten möchten, und den Problemen, die Sie lösen möchten. Erfahren Sie, wie sie datengetriebene Entscheidungen fällen können, indem Sie Fallstudien durcharbeiten, die veranschaulichen, wie man Modelle identifiziert, anpasst und bewertet, die für das Erreichen Ihres Analyseziels am nützlichsten sein könnten. (view in ...
Video using JMP Pro 18 was posted in May 2025. Are you responsible for making decisions about chemical processes or products based on large amounts of messy data? Is your data in multiple formats received from samples or from inline or offline laboratory equipment? Do you need to relate measurements made on a chemical system to a state or property of the system? Are you a chemical analyst on a t...
Video using JMP 18 was posted in May 2025. Do you want to use predictive models and need to understand or review the basics first? Have you tried predictive modeling and are a bit usure whether to accept the accuracy of models you develop? Are you relying on extrapolation because you can’t measure above or beyond certain limits? In this session Mastering JMP session, we explore tools in JMP and ...
Video was recorded in March 2025 using JMP 18. Are you looking for ways to determine an effective way to trade off power and speed to find a sweet spot for your semiconductor chip design? Are you an engineer responsible for designing or doing validation testing to assure that your hardware solutions satisfy the requirements or your customers? Do you seek efficient ways to predict the behavior of a...
Video was recorded in February 2025 using JMP 18. Do you need to formulate drug products to match a specific dissolution profile? Do you need to re-formulate or validate that changes in raw material suppliers do not change a drug's dissolution profile? Do you develop dissolution methods for product release? In this session, we will: Compare a new formulation's dissolution profile to an existing ...
Video was recorded in February 2025 using JMP 18. Least Squares Regression is often the go-to method for building statistical models. But should it be? Quality measures, like defect counts that are used as response variables, often violate assumptions that must be met for standard least squares regression models to be successful. What should we use instead? In this session, we use the followin...
Découvrez comment analyser des données de mesures séquentielles lorsque les mesures que vous souhaitez analyser en tant que réponses ne sont pas des points uniques, mais une gamme de points présentés sous forme de courbes. Il peut s'agir, par exemple, de spectres chimiques, de capteurs et de données par lots ou en flux. Apprenez à utiliser efficacement l'ensemble des données plutôt que des points ...
Erfahren Sie, wie Sie sequenzielle Messdaten analysieren können, bei denen es sich nicht um einzelne Punkte, sondern um eine Reihe von Punkten handelt, die als Kurven dargestellt werden. Beispiele hierfür sind chemische Spektren, Sensoren und Batch- oder Streaming-Daten. Erfahren Sie, wie Sie den gesamten Datenbereich anstelle ausgewählter Punkte in der Kurve effizient nutzen können, um sofort int...
Video was recorded in January 2025 using JMP 18. Do you have historical or real time production data? Have you wondered how to leverage these data to design high value, efficient, cost-effective experiments? In this session, we will use the following steps to find an optimal process recipe for a plasma enhanced chemical vapor deposition (PECVD) tool that is used to deposit an insulative layer on a...
Lernen Sie, Modelle mit Hilfe von Variablenauswahltechniken anzupassen, einschließlich Schrumpfungstechniken, die speziell auf die Modellierung korrelierter und hochdimensionaler Daten ausgerichtet sind. Erfahren Sie, wie Sie mit der eine Vielzahl von Verteilungen für Antworten untersuchen können, die kontinuierlich, binomial, zählend oder null-inflationär sind, und wie Sie Modelle vergleichen kön...
Get JMP software free for academic use at jmp.com/student Real-world data can be highly multivariate, and students in statistics, data science, and the physical and social sciences should be equipped to analyze such data with appropriate multivariate statistical methods. JMP software can make learning multivariate methods more accessible and engaging to students through its interactive, no-co...
Découvrez comment ajuster des modèles à l'aide de techniques de sélection de variables, y compris des techniques de réduction qui traitent spécifiquement de la modélisation de données corrélées et en haute dimension. Découvrez comment utiliser la régression généralisée de JMP Pro pour examiner toute une série de distributions pour les réponses continues, binomiales, de comptage ou avec excès de zé...
Get JMP software free for academic use at jmp.com/student Real-world data can be highly multivariate, and students in statistics, data science, and the physical and social sciences should be equipped to analyze such data with appropriate multivariate analysis methods. JMP statistical software can make multivariate methods more accessible and engaging to students through its interactive, no-co...
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Video was updated in August 2024. Q&A is included after time 30:00. Text Explorer is useful for exploring unstructured text, such as survey free-response fields or incident reports, to understand its meaning. This is often an iterative process, where you alternate between curating and analyzing a list of terms and phrases. (view in My Videos) See two case studies (Europe Vacation and Which W...
See how to use a prediction model to find optimum conditions (set points and ranges) to use the model to make decisions. See how to: Find optimum set points Optimize desirabilities Identify the combination of factor settings that will optimize the response Define desirabilities Remember settings Lock factor settings (reset factor settings) Simultaneously optimize multiple responses, includ...
See how to use JMP to analyze biological assays during pharmaceutical and biotechnology development to help prepare for regulatory submissions, develop standard operating procedures and maintain good manufacturing practices. Build and analyze parallelism between a pair of doses and responses, estimate relative potency, determine when a drug dose or concentration reaches toxicity, determine the aff...
See how to use JMP and JMP Pro to identify important predictors suitable to predictive modeling, reducing variance caused by estimating unnecessary terms, and building predictive models. See case studies that show how to use JMP Stepwise Regression to find important variables and active model effects and how that approach compares to JMP Pro Generalized Regression techniques that automatically inc...
JMP 18 offers new Fatigue Model capabilities that implement a new methodology, based on years of research from Prof. William Meeker and a team of researchers, for analyzing fatigue testing data (also known as S-N data). The new methodology respects the nature of censoring in fatigue testing data; unifies the theory of inferring fatigue life distribution and fatigue strength distribution; and estab...
Erfahren Sie, wie Sie sequenzielle Messdaten analysieren können, bei denen es sich nicht um einzelne Punkte, sondern um eine Reihe von Punkten handelt, die als Kurven dargestellt werden. Beispiele hierfür sind chemische Spektren, Sensoren und Batch- oder Streaming-Daten. Erfahren Sie, wie Sie den gesamten Datenbereich anstelle ausgewählter Punkte in der Kurve effizient nutzen können, um sofort int...
Get JMP software free for academic use at jmp.com/student Analysis of time-to-event data – often called survival or reliability analysis – is commonly taught in biostatistics, reliability engineering, and other domains. JMP’s suite of survival and reliability tools support comprehensive teaching of key concepts and techniques in this domain, including survival and hazard functions, censor...
Get JMP software free for academic use at jmp.com/student Unstructured text data is everywhere, and modern analytics and data science education is increasingly covering text mining techniques. Text Explorer in JMP and JMP Pro enables students to learn basic and advanced text mining methods through an interactive, no-code interface, making text mining approachable to a wide range of students a...
One of the most significant roles of the Medical Monitor is conducting safety data reviews to evaluate the presence or lack of safety issues with respect to the treatment the subjects receive. Reviews are conducted throughout the study, from Phase 1 through Phase 4. Not only are reviews required by regulators, but they are necessary to ensure the safety of participants. By following subjects as th...
Get JMP software free for academic use at jmp.com/student JMP Pro 17 marked a significant change in how genomic data analysis is performed in JMP. New platforms were introduced for genetic marker analysis and breeding simulations, and several existing platforms were optimized for the handling of large, wide data sets. Unlike the specialized JMP Genomics software, these new features are built ...
Get JMP software free for academic use at jmp.com/student Multivariate statistical methods are taught across a range of disciplines, from chemistry to psychology and more. JMP makes many basic-to-advanced multivariate methods accessible to students through its interactive, no-code interface. This webinar is the second in a two-part series on teaching multivariate methods in JMP. It demonstr...
Get JMP software free for academic use at jmp.com/student Multivariate statistical methods are taught across a range of disciplines, from chemistry to psychology and more. JMP makes many basic-to-advanced multivariate methods accessible to students through its interactive, no-code interface. This webinar demonstrates tools and techniques for teaching two common multivariate techniques: mult...
「JMPをマスターしよう 主成分分析/クラスター分析 編」の動画をご視聴いただけます。 2022年10月に実施したWebセミナーのオンデマンドバージョンです。オンデマンド用にセミナー内容を再構成しており、JMPによる主成分分析、クラスター分析の実行方法、レポートの解釈やオプション、便利な機能について紹介しています。動画は2つのチャプター（Chapter1、Chapter2）で構成され、各チャプターは、3つのセクション（Section1～Section3）に分かれております。動画で用いているJMPのデータは公開しておりません。同様の操作をJMPに搭載されている以下のサンプルデータで実行できます。 •「Solubility.jmp」 •「Birth Death Subset.jmp」 •「Cytometry.jmp」 Chapter 1: 主成分分析とJMPの利用Chapter 2: ク...
関数データエクスプローラの概要と関数主成分分析（5分34秒）利用例１：関数データを用いたサンプルの分類 （16分52秒）利用例2：関数データを用いた特性値の予測（12分49秒）利用例3：関数応答実験計画（11分27秒）利用例4：スペクトルデータの分析（12分29秒） 「関数データエクスプローラ」（FDE; Functional Data Explorer）プラットフォームは、関数データ・シグナルデータ・時系列データを分析するためのプラットフォームです。関数データに対し、特徴を表す関数主成分を抽出して次元縮小をおこない、関数データの判別、予測モデルの作成などを行なえます。 本動画に関する資料（PDF) をダウンロードできます。 関数データエクスプローラの概要と関数主成分分析（5分34秒） 関数データについて、関数データの特徴量として関数主成分を抽出すること。この後に説明する、利用例1～利...
Mixed Modeling has been the standard for analyzing data with more than one source of random variation (blocking, split-plots, etc.). The Linear Mixed Model (LMM) assumes the response is continuous with no bounds. If your response is a discrete count, binary response or a proportion in terms of y/n, use the Generalized Linear Mixed Model (GLMM). (view in My Videos) See how to: Undere...
Structural Equation Modeling provides a general analysis framework for investigating associations between observed and unobserved variables. Numerous models can be fit within this flexible framework. This flexibility comes from the ability to model variances, covariances, and means in observed data. This tutorial video includes information and Q&A about the purposes, approaches, and statistica...
Learn to use statistical tools to explore and describe multidimensional data. Quickly and easily identify correlations between variables. Uncover and remove outliers to prevent them from biasing results, or extract them for further investigation. Group observations that are most similar to each other, and reduce the number of variables in a dataset to describe features in the data and simplify su...
Video was updated for JMP 18 June, 2024. The JMP Prediction Profiler is an option available from over 20 places in JMP to use DOE, observational and formula data to visualize and explore models and make decisions. (view in My Videos) See how to: Understand the purpose of Prediction Profiler, types of data that can be profiled, and how to access the ProfilerExplore the Opportunity Space Term...
Scopri come usare strumenti statistici per esplorare e descrivere dati multidimensionali, identifica rapidamente le correlazioni tra variabili e individua e rimuovi gli outlier per evitare che producano risultati distorti, oppure estraili per ulteriori analisi. Raggruppa le osservazioni più simili tra loro e riduci il numero di variabili in un data set per descrivere le caratteristiche principali...
Lernen Sie die Verwendung statistischer Werkzeuge, um mehrdimensionale Daten zu untersuchen und zu beschreiben. Erkennen Sie Korrelationen zwischen Variablen schnell und einfach. Entdecken und entfernen Sie Ausreißer, um eine Verzerrung der Ergebnisse zu vermeiden, oder extrahieren Sie diese zur weiteren Untersuchung. Gruppieren Sie Beobachtungen, die einander am meisten ähneln, um die Anzahl der...
Get JMP software free for academic use at jmp.com/student This webinar demonstrates the many resources and tools available in JMP to help you incorporate cluster analysis into your curriculum. We review JMP's clustering tools, which include k-means, hierarchical clustering, and more, as well as how to use these tools effectively for teaching. We also see how the interactive and graphical natu...
「JMPをマスターしよう 日付・時間データの分析編」の動画をご視聴いただけます。 2022年6月に実施したWebセミナーのオンデマンドバージョンです。オンデマンド用にセミナー内容を再構成しており、JMPによる日付・時間データの効果的な可視化機能、時系列データ分析の機能について紹介しています。動画は2つのチャプター（Chapter1、Chapter2）で構成され、各チャプターは、3つのセクション（Section1～Section3）に分かれております。動画で用いているJMP形式のデータ（.jmp）は、本ページ上側にあるリンクよりダウンロードできます。 Chapter 1: JMPによる日付・時間データの扱い方、効果的な可視化方法Chapter 2: JMPによる時系列予測 ～ARIMAモデル、状態空間平滑化モデル～ ※本セミナーは、動画作成時点（2022年8月）の最新バージョ...
Get JMP software free for academic use at jmp.com/student Many research studies involve testing for and quantifying the differences between treatments. These studies could consist of a simple A/B comparisons of a single factor all the way to exploring the impact that multiple factors including their potential interactions have on an outcome. In this webinar, a statistical scientist from JMP...
This technical presentation includes examples presented in JMP for Mixed Models. Data from the book used in the presentation is included. The video is over 90 minutes long with questions interspersed throughout. This tutorial and examples of regression, random coefficient and multi-level models all require JMP Pro. Part 3 will be scheduled for early 2022 and will cover assessing power and precisi...
This technical presentation was given by Elizabeth Claassen, JMP Statistical Developer and co-author of JMP for Mixed Models for JMP. Data from the book was used in the presentation and is available for you to download and use. The video is over 90 mins. long with questions interspersed throughout. Mixed models are one of the most powerful ways to handle correlated observations in designed ex...
Background: Simple Linear Regression assume errors (and response) are normal, but when normality isn't the case, predictions may fall outside of meaningful range (maybe not a big deal) and inference is not reliable (probably a bigger deal)Generalized Linear Models (GLM) assume some other distribution than normality, for example for: Count data (e.g., number of defects on a product) Skewed data (...
DOE allows multiple input factors to be manipulated, determining their effect on a desired output (response). By manipulating multiple inputs at the same time, DOE can identify important interactions that may be missed when experimenting with one factor at a time. Generalized Regression used in conjunction with a designed experiment may provide answers to questions such as: What are the key fac...
(view in My Videos) See how to: Use repeated measures to model correlation structuresOrganize data, graph correlations, build models, compare/select the best model and test hypothesesInterpret statistics related to mix modelsUnderstand Toeplitz, ante-dependent and compound symmetry (equal variances) covariance structures Deploy AR(1) model that assumes degradation rate constancy over timeDepl...
See how to: Understand the basics of SEM Confirmatory Factor Analysis (CFA) – a multivariate statistical procedure to test how well measured variables represent the number of constructs and confirm or reject a theory Path Analysis - an extension of the regression model built from the correlation matrix that compares two or more casual models and...
(view in My Videos) See how to: Launch Time Series Forecasting specialized modelingUnderstand how a recommended set of models are automatically fit to the time series and how optimal models are used for forecastingSelect and interpret forecast settings, including NAhead, Period, NHoldout, Preserve Model Selection Criterion, Forecast Interval Level and Imputation for Applicable ModelsInterpre...