- JMP®: A Case Study Approach to Data ExplorationThis course is designed as the first step for those who want to use JMP to explore, manage, and analyze data. It is recommended as a prerequisite for many of our other courses.
- JMP®: Graphing and Reporting with JMP®This course is designed for anybody who wants to create compelling graphs, reports, and dashboards that effectively share the story in their data.
- JMP®: Statistical Decisions Using ANOVA and RegressionThis course teaches you how to use analysis of variance and regression methods to analyze data with a single continuous response variable, and introduces statistical model building.
- Statistical Thinking for Industrial Problem SolvingThis course is for anyone seeking to develop core competency in applied problem-solving with data and statistics. It addresses the Statistical Thinking for Industrial Problem Solving certification exam content areas and tasks.
Design of Experiments and Quality Improvement
- JMP®: Custom Design of ExperimentsThis course focuses on the core principles of designing an experiment, enabling you to understand and apply those principles to achieve an optimal design using the Custom Design platform in JMP.
- JMP®: Classic Design of ExperimentsThis course teaches you how to design and analyze experiments in JMP to find the vital few factors or optimize the process response. The course emphasizes the principles of experimental design while demonstrating classic approaches to screening designs and response surface designs.
- JMP®: Design and Analysis of Mixture ExperimentsThis course is for JMP users who deal with mixture or formulation experiments. The course demonstrates how to use various approaches to create an appropriate experimental design for commonly encountered mixture situations. The analysis of mixture experiments is also covered, including finding the optimum formulation.
- JMP®: Modern Screening DesignsThis advanced course presents strategies and methods, using JMP, for designing experiments to screen many factors in an optimal study, as well as several specialized analytical tools that respect the limited information available in such experiments.
- JMP®: Measurement Systems AnalysisThis course teaches you how to determine the measurement error associated with your process, including both measurement system variability and bias, using JMP software.
- JMP®: Statistical Process ControlThis course teaches you how to set up and maintain a statistical process control system using JMP software.
- JMP®: Reliability Analysis for Non-Repairable SystemsThis course is for anyone who needs to analyze data, using JMP, about how long an object (reliability) or person (survival) operates within acceptable parameters ("time to event"). The course is presented using manufacturing examples, but those interested in survival analysis or studying recidivism will also find the course useful.
Advanced Topics and JMP Pro
- JMP® Pro: Analyzing Curves and Profiles Using the Functional Data ExplorerThis course helps you recognize and model functional data. It teaches you to use the data as a response, such as the outcome for a designed experiment, or as new covariates or features, such as in a multivariate analysis. Functional data are defined as a function, profile, or curve. They are a series of observations over time or any other continuous variable. These data can be modeled so that changes in the shape can be associated with changes in other variables.
- JMP® Pro: Finding Important PredictorsThis course teaches you techniques for fitting statistical models to identify important variables. Manual, graphical, and automated variable selection techniques are presented, along with advanced modeling methods. The demonstrations include modeling both designed and undesigned data.
- JMP® Pro: Predictive ModelingThe course covers the skills required to develop, assess, tune, compare, and score predictive models using JMP Pro software.
- JMP®: Analyzing and Modeling Multidimensional DataThis course is for JMP users who work with data that have many variables. The course demonstrates various ways to examine high-dimensional data in fewer dimensions, as well as patterns that exist in the data.
- JMP®: Analyzing Discrete ResponsesThis course teaches you how to analyze discrete (or categorical) data or outcomes using association, contingency tables, stratification, correspondence analysis, logistic regression, generalized linear models, partitioning, and artificial neural network models.
JMP Scripting Language
- JMP®: The JMP® Scripting LanguageThis course is for JMP users who want to extend JMP software's functionality using the JMP Scripting Language (JSL) to automate routine tasks, extend or create new procedures, and customize reports.
- JMP®: Designing and Building a Complete JMP® ScriptThis course teaches you how to approach writing a new script in a methodical way. A realistic case study is used to illustrate the typical steps. A separate case study is developed in the course exercises.
Business Knowledge Series
- JMP®: Design of Experiments for Mixtures Using Machine LearningThis course teaches you how to design and analyze experiments in JMP to find the vital few factors or optimize the process response. The course emphasizes the principles of experimental design while demonstrating classic approaches to screening designs and response surface designs.
- Quality by Design (QbD) Using JMP®This course focuses on how to establish a systematic approach to pharmaceutical development that is defined by Quality-by-Design (QbD) principles using design of experiments (DOE).
Don’t see a course you want listed on dates you need? Want to be notified the next time a specific course is added to the public training schedule?
- JMP Scripting Language JMP®: The JMP® Scripting Language April 3 - 7 | 1:00 - 4:30 p.m. ET
- Getting Started JMP®: A Case Study Approach to Data Exploration April 4 - 5 | 1:00 - 4:30 p.m. ET
- Advanced Topics and JMP Pro JMP® Pro: Predictive Modeling April 17 - 20 | 1:00 - 4:30 p.m. ET
- Getting Started JMP®: Statistical Decisions Using ANOVA and Regression April 24 - 27 | 1:00 - 4:30 p.m. ET
- Design of Experiments and Quality Improvement JMP: Reliability Analysis for Non-Repairable Systems May 1 - 4 | 1:00 - 4:30 p.m. ET
- Design of Experiments and Quality Improvement JMP®: Statistical Process Control May 22 - 25 | 1:00 - 4:30 p.m. ET