Training

Our training leaders are subject matter experts who have deep experience in technical training and industry knowledge across various sectors. We have trained thousands of engineers, scientists, and researchers worldwide to apply advanced analytics and statistical methods effectively in their daily work. We deliver engaging and interactive training sessions with dynamic illustrations and practical tips that are tailored to our clients’ real-world problems.

Customized Training Available

We can customize our 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.

Complimentary Training Offerings by JMP Software

To complement our training courses, JMP software offers a number of learning opportunities including the Statistical Thinking for Industrial Problem Solving online course. JMP has also created the Statistics Knowledge Portal, a free introduction to statistics for those seeking to master statistical concepts.

JMP Training Courses

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

Data Analysis and Statistics Using JMP Software for Engineers and Scientists

This 3-day course is the most popular of our standard 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 real-world scenarios.

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 the benefits of 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, such as Microsoft Excel, 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 visually and interactively
  • Create summaries, tables, charts, and graphs in the JMP software application
  • 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 Software

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

Standard Courses DOE 1 and DOE 2

Design of Experiments 1 Using JMP Software and Design of Experiments 2 Using JMP Software, which are described in more detail below, are geared to engineers and scientists. These courses are the most popular of our training courses on the subject of DOEs.

Alternative Course to DOE 2

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

 

Design of Experiments 1 Using JMP Software

This course provides a solid foundation on how to apply DOE using JMP software effectively in your research. The methods in this 2-day course 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 software

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 Software

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

Does batch processing in a manufacturing environment pose a challenge to designing ordinary experiments? Did you discover that your response doesn’t increase or decrease in a straight line like all those classroom examples? Do you need some direction on 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 software 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 Software course, or equivalent experience in statistics and JMP software

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 Software

This training course is an alternative to Design of Experiments 2 Using JMP Software. It’s geared to 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, being unaware that it is then impossible to get correct statistical tests out of the results.

The correct assumption is that batch processing requires batch-processing DOEs. Design the experiments with batch processing considerations from the start. The analysis will then change accordingly 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 hard-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 Software course, or equivalent experience in statistics and JMP software

Expected Results

After completing this course, participants will be able to:

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

 

Design for Six Sigma (DFSS)

This comprehensive 12-day course provides participants with everything they need to conduct process design for six sigma. It is intended to support participants who are working directly on DFSS projects. Interactive exercises are used throughout the course to engage participants in learning process design and applying the concepts to their daily work. Handout materials include worksheets and templates.

Who Should Attend

Engineers, scientists, and technicians who require a comprehensive course to help them make design improvements to products and/or processes

Duration

12 days in total, and topics are divided into 3 sessions

Prerequisites

General familiarity with computers and spreadsheet software, such as Microsoft Excel, is helpful. This course requires the use of JMP software.

Expected Results

After completing this course, participants will be able to:

  • Write project charters
  • Capture requirements to define the voice of the customer
  • Produce quality function deployment (QFD) / House of Quality diagrams
  • Conduct failure mode effects and analyses (FMEA/risk management)
  • Use mistake-proofing techniques in manufacturing processes
  • Apply statistical analyses, including:
    • Hypothesis testing
    • Confidence intervals
    • Statistical process control
    • Process capability (normal and non-normal)
    • Measurement system analysis
    • Simple and multiple linear regression
    • Sampling plans
  • Use machine learning algorithms to create predictive models with design and observational data
  • Design and analyze various types of experiments, including mixtures
  • Create robust designs
  • Set ranges of tolerance limits
  • Build design scorecards
  • Integrate multi-objective optimization in process design
Design for Six Sigma (DFSS) LITE

This 5-day course is a condensed, yet comprehensive, version of our Design for Six Sigma (DFSS) 12-day course. DFSS LITE is geared to participants who are unable to attend the 12-day course and wish to learn about DFSS principles in a shorter timeframe.

This course is designed to support participants who are working directly on DFSS projects. Interactive exercises throughout the course will enable students to grasp the concepts more readily. Handout materials include worksheets and templates.

Who Should Attend

Engineers, scientists, and technicians who design processes and/or products and would like to make improvements to their current design practices

Duration

5 days

Prerequisites

General familiarity with computers and spreadsheet software, such as Microsoft Excel, is helpful. This course requires the use of JMP software and working knowledge of ANOVA, Regression, hypothesis testing, and other basic statistical methods.

Expected Results

After completing this course, participants will be able to:

  • Write project charters
  • Capture requirements to define the voice of the customer
  • Produce quality function deployment (QFD) / House of Quality diagrams
  • Conduct failure mode effects and analyses (FMEA/risk management)
  • Use mistake-proofing techniques in manufacturing processes
  • Design and analyze various types of experiments
  • Create robust designs
  • Set ranges of tolerance limits
  • Build design scorecards
  • Integrate multi-objective optimization in process design
Just Enough Design of Experiments for Managers and Operators

Designs of Experiments (DOEs) 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 Software

How do you determine that the signals you get in your analysis are from the system of interest? Is it possible that the signals are 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 Software 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 Software

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 Software 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

Are you interested in writing your own custom scripts or programs in JMP development? Even though programming in JMP Scripting Language (JSL) can be quite challenging (it’s not for everyone), it can be configured to help JMP users to become more productive. There are plenty of opportunities for JMP users, even in basic features and functions, to make their lives easier with the use of JSL. This 1-day course will boost your productivity in using JMP software!

Who Should Attend

Anyone who is interested in learning to program in JSL

Duration

1 day

Prerequisites

Data Analysis and Statistics Using JMP Software 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 to learn because it’s more than just a programming language. Programming in JSL means having to configure the nuts and bolts that actually make up JMP functionality. Since JMP was not originally designed to support the functions and methods of a programming language, making the leap to advanced JSL may present 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

Intermediate experience in using JMP software

At least several months experience in using basic JSL is strongly recommended.

Expected Results

After completing this course, participants will be able to:

  • learn the expected behavior of the JMP software application
  • 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 Software

Would you like 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? Every processing operation should dedicate resources to identifying and reducing sources of variation.

Reducing variation is its own reward because subsequent areas of improvements will be much easier to determine. We find that most engineers and analysts who work in manufacturing spend considerable time in responding to problems and incidents. We recommend that every manufacturer assign a dedicated group that is tasked with reducing variation, which will uncover practical insights and lead to fewer incidents.

Who Should Attend

Engineers who are working to reduce variation in a manufacturing facility

Duration

1 day

Prerequisites

Data Analysis and Statistics Using JMP Software 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

 

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