Our Integrated Approach to Training

Advance your proficiency in using JMP® software's analytics and visualization features with instructor-led training from our experts

JMP Training Courses

Our JMP experts have deep experience in technical training and industry knowledge across various sectors. We can customize our JMP training courses to meet your curriculum and offer flexible scheduling to suit your timetable.

We look forward to discussing your particular training needs for your organization. For more information, please contact us.

Curriculum


To view more details about our training courses, click on the topic headings below.

Data Analysis and Statistics Using JMP for Engineers and Scientists

This 3-day course is the most popular of our training courses. It combines the use of JMP software with basic, intermediate, and advanced analytical methods, including descriptive statistics, graphical analysis, hypothesis testing, analysis of variance, and model building. Interactive illustrations enable participants to understand statistical concepts by engaging and experimenting with them. For guidance, a set of flowcharts is provided for integrating JMP tools into a process that shows participants where they are, where they are going, and when they have fully completed the analysis.

This course also includes specific advice on how to reap the benefits of these methods in the real world.

Taking this course in 3 consecutive days leads to higher retention, better understanding of how the methods relate to one another, and more opportunity to harness statistical methods right away.

Who Should Attend

Engineers, scientists, and technicians who intend to make improvements to products and/or processes

Duration

3 days

Prerequisites

General familiarity with computers and spreadsheet software is helpful.

Expected Results

After completing this course, participants will be able to:

  • import and arrange data for analysis including JMP productivity features for data tables
  • overcome challenges in data format with a variety of JMP tools
  • explore data
  • create summaries, tables, charts, and graphs interactively in JMP
  • solve a variety of scientific and engineering problems from single to multiple factors and responses
  • learn how to recognize and overcome statistical challenges
  • describe and analyze the distribution of data
  • understand issues related to sampling and calculate appropriate sample sizes
  • generate and analyze statistical intervals and hypothesis tests to make data-driven decisions
  • complete univariate, bivariate and multivariate analyses using both continuous and categorical factor variables
  • identify problems with analyses, such as violating statistical assumptions, and how to solve them
  • convert data from analyses into presentations.


Course Series: Design of Experiments Using JMP

Design of Experiments (DOE or DOX) is perhaps the most effective and efficient way to do research today. Engineers and scientists who engage in design of experiments will be able to advance the competitiveness of their organizations by discovering deeper insights in less time and at lower cost.

Most DOEs have one or more of the following objectives:

  • determine and fix which factor is causing problems
  • determine the range allowance of the process, especially in relation to control limits and specification limits (Sensitivity Testing)
  • determine which path to take in development
  • figure out how to reduce variation
  • try out proposed ideas and see if they lead to improvement
  • test settings for lower-cost factors
  • find ways to compensate for changes in one condition or material while maintaining the integrity of all other data

The two-course series, Design of Experiments 1 Using JMP and Design of Experiments 2 Using JMP, is geared towards engineers and scientists. These courses are the most popular of our training courses on the subject of DOEs.

A shorter and more focused alternative to Design of Experiments 2 Using JMP is the Design of Experiments for Batch Processes and High-Throughput Screening Using JMP course.


Design of Experiments 1 Using JMP

The methods in this 2-day course alone will advance research and improve productivity considerably over informal methods.

Who Should Attend

Engineers, scientists, and technicians who are involved in characterizing, evaluating, and improving processes and equipment

Duration

2 days

Prerequisites

Data Analysis and Statistics Using JMP for Engineers and Scientists course, or equivalent experience in statistics and JMP

Expected Results

After completing this course, participants will be able to:

  • design experiments to maximize efficiency and analytical power while being practical
  • develop a strategy for experimentation
  • apply the scientific method
  • design, analyze, and interpret screening experiments

Design of Experiments 2 Using JMP

This course extends beyond Design of Experiments 1 with JMP to focus on some very effective and advanced DOE techniques. Some of these advanced methods have been made widely available with software over the past 10 years.

Does batch processing in a manufacturing environment make designing ordinary experiments a challenge? Did you discover that your response does not increase or decrease in a straight line like all those classroom examples? Want to know what to do next?

This 2-day class provides an introduction to the practice of experimentation for process optimization. Topics include response surface designs, split-plot designs, strip-plot designs, and computer-aided (optimal) designs. Topics on analysis and interpretation integrate the use of JMP to support analysis of variance and multiple linear regression analyses.

Who Should Attend

Engineers, scientists, and technicians who are involved in characterizing, evaluating, and improving processes and equipment

Duration

2 days

Prerequisites

Design of Experiments 1 Using JMP course, or equivalent experience in statistics and JMP

Expected Results

After completing this course, participants will be able to:

  • implement the Path of Steepest Ascent method of designing experiments
  • design, analyze, and interpret experiments in response surface methodology
  • understand the complexity of doing experimental design in a batch-processing environment
  • understand the costs and benefits of performing an optimal experiment
  • conduct mixture design of experiments
  • understand and apply robust optimization

Design of Experiments for Batch Processes and High-Throughput Screening Using JMP

This training course is an alternative to Design of Experiments 2 Using JMP. It’s geared towards engineers and scientists who prefer a shorter and more focused examination of batch processing designs.

In the semiconductor and pharmaceutical industries, batch processing is the norm. Batch sizes change from step to step within the process. A single unit in one step is only part of a unit in another step. Many measurements can often be made on what is essentially one object being measured. Traditional full and fractional factorial designs applied in these batch situations often lead to misleading results. Engineers limit the randomization of a traditional DOE design, unaware that it is then impossible to get correct statistical tests out of the results.

The right thinking is to realize that batch processing requires batch-processing DOEs. Design the experiments with batch processing in mind from the beginning. The analysis changes along with the designs.

Course Description

This course is the next step after understanding basic full and fractional factorial designs.

Does batch processing in a manufacturing environment make designing ordinary experiments a challenge?

Are some factors hard to vary? For example, a hard-to-vary factor would be difficult to change randomly, as suggested by most experimental designs.

Are you doing experiments repeatedly over multiple process steps?

Repeated instances of hard-to-vary factors or experiments over multiple process steps are strong indicators of batch processing. It is possible to correctly take into account difficult-to-vary factors and multiple processing steps in the design and analysis of DOEs.

Who Should Attend

Engineers, scientists and technicians who will design and analyze batch-processing experiments

Duration

1 day

Prerequisites

Design of Experiments 1 Using JMP course, or equivalent experience in statistics and JMP

Expected Results

After completing this course, participants will be able to:

  • understand the necessity of replication in batch processing
  • design split-plot designs in JMP
  • design basic strip-plot designs in JMP
  • design complex strip-plot designs with JMP as a tool
  • build correct models for strip-plot and split-plot designs in JMP
  • analyze strip-plot and split-plot designs in JMP


Just Enough Design of Experiments for Managers and Operators

Designs of Experiments (DOEs) don’t happen in a vacuum and require managerial approval and operator support. This accessible 1-day course will provide you with just enough information on how DOEs work by using graphs instead of a lot of statistical jargon.

Who Should Attend

Managers, operators, and anyone else who is interested in how DOEs work

Duration

1 day

Prerequisites

Commonly used computing skills and some familiarity with Microsoft Excel

Expected Results

After completing this course, participants will be able to:

  • adjust practices and policies to support effective DOEs
  • participate in designing a DOE
  • provide a warning for problems before and during a DOE


Gauge Studies, MSA, and Advanced Metrology Setup and Control Using JMP

Are you sure that the signals that you get in your analysis are from the system of interest or could they be from faults within the measurement system itself?

This 1-day course provides an introduction to the studies of measurement systems analysis. Topics covered include determining the factors to study, conducting the study, and using graphical and numerical analysis to summarize the results.

Who Should Attend

Engineers, scientists, and technicians who are involved in evaluating metrology tools

Duration

1 day

Prerequisites

Data Analysis and Statistics Using JMP for Engineers and Scientists course, or equivalent experience in statistics and JMP. Some basic knowledge of Design of Experiments would be helpful, but is not strictly necessary.

Expected Results

After completing this course, participants will be able to:

  • design and analyze a gauge study
  • explore linearity and bias
  • identify and correct problem areas involved in measurement
  • determine whether changes to the measurement system lead to improvement
  • conduct an MSA with fixed and random factors
  • conduct an MSA with crossed and nested data arrangements


Improving Process Behavior with Statistical Process Control Using JMP

This 1-day course provides an introduction to Statistical Process Control (SPC). Topics covered include historical SPC, passive data collection, sampling plan determination, control-limit calculation for continuous processing and batch processing, and out-of-control action plans.

Who Should Attend

Engineers, scientists, and technicians who are involved in process control

Duration

1 day

Prerequisites

Data Analysis and Statistics Using JMP for Engineers and Scientists course, or equivalent experience in statistics and JMP

Expected Results

After completing this course, participants will be able to:

  • perform passive data collection and determine significant sources of variability
  • determine the correct set of control charts for their process
  • calculate the correct control limits on the process
  • determine whether a change in process conditions has lead to an improvement in process behavior
  • know when to fix control limits
  • know how to rationally subgroup
  • conduct SPC for variable and attribute data


JMP Scripting Language that Every JMP User Should Know

Interested in writing your own scripts or programs in JMP? Want to do things your own way?

JMP scripting language (JSL) can be quite challenging–it’s not for everyone. But just about every JMP user is looking for ways to be more productive. There are plenty of opportunities, even among the basics, for JMP users to make their lives easier with JSL. This 1-day course will boost your productivity!

Who Should Attend

Anyone who is interested in learning to program in JSL

Duration

1 day

Prerequisites

Data Analysis and Statistics Using JMP for Engineers and Scientists course, or equivalent experience in statistics and JMP. Experience in using JMP weekly for at least 1 year is recommended.

Expected Results

After completing this course, participants will be able to:

  • save scripts from graphs and summary tables
  • tie together multiple scripts
  • select and rearrange specific items from reports
  • write loops
  • write scripts that ask for user input


Advanced JMP Scripting Language

JMP scripting language (JSL) is not the easiest language to learn because it’s more than a language. Programming in JSL means playing with the bits and pieces that actually make up JMP. Since JMP was not designed to be a programming language, this can lead to some challenges.

This 3-day course provides an introduction to advanced JSL. Topics covered will be messaging, tables, matrices, functions, graphics, platforms, communication with the user, and accessing databases.

Who Should Attend

Engineers, scientists, and technicians who are JMP power users, have an aptitude for programming, and wish to create substantial applications for other users

Duration

3 days

Prerequisites

JMP Scripting Language that Every JMP User Should Know course, or equivalent basic JSL experience.

Significant JMP use.

At least several months of basic JSL use is strongly recommended.

Expected Results

After completing this course, participants will be able to:

  • find out how JMP behaves
  • write, debug, and run JMP scripts
  • learn two ways of making scripts abstract and general so that they are self-maintaining and widely applicable


Variation Reduction Using JMP

Want to reduce the variation in your manufacturing process? What are your biggest sources of variation? Where would your efforts be most effective if you were to reduce some of the variation?

In simple terms, every processing operation should dedicate resources to identifying and reduce sources of variation.

Reducing variation is its own reward because subsequent improvements will be much easier to find. We find that most engineers and analysts working in manufacturing spend considerable time in responding to situations. We recommend that every manufacturer form a group that is largely focused on reducing variation, which will uncover practical insights and lead to fewer incidents to be addressed.

Who Should Attend

Engineers who are working to reduce variation in a manufacturing facility

Duration

1 day

Prerequisites

Data Analysis and Statistics Using JMP for Engineers and Scientists course, or equivalent experience in statistics and JMP. Some basic knowledge of Design of Experiments would be helpful, but is not strictly necessary.

Expected Results

After completing this course, participants will be able to:

  • calculate variance components
  • understand and communicate variance components
  • use variance components to aid in reducing variation in process and product
  • use variance components to choose the minimum necessary sampling plan for control charts