Menu

Training Courses

Create your own custom learning program for on-site or remote on-site training by choosing from the courses below. Many courses are part of our prescribed learning tracks and are also offered as public training sessions.

Industry-Specific Options

Our Training courses are divided into several series. Manufacturing and Services cover similar statistical methods but their course materials use different industry-based examples. The Automating Analyses in Minitab course applies to any series. The Predictive Analytics series focuses on building predictive models using examples from both manufacturing and service industries.

Many courses have prerequisite classes. Please contact us if you have any questions about which courses are right for you or to schedule training.

Manufacturing

Our Manufacturing Quality series is for professionals working in the automotive industry, chemical production plants, and other companies involved in manufacturing. The course materials include examples with metrics such as diameter, pressure, and hardness.

Services

Our Service Quality series is for professionals working in financial services, retail and other service-related industries. The course materials include examples with metrics such as time, ratings, and revenue. 

Predictive Analytics

Our Predictive Analytics series is for professionals working in any industry doing predictive modeling. The course materials include examples with metrics such as payment performance, time, revenue, volume and quality grade.

Medical Devices

Our Medical Devices series is for professionals working in the Medical Device industry. The course materials include examples with metrics such as breaking strength, diameter, particle size, nonconformities, and moisture.

Pharmaceuticals

Our Pharmaceuticals series is for professionals working in the Pharmaceutical industry. The course materials include examples with metrics such as cycles to failure, active ingredient, concentration, nonconformities, and fill weight.

Healthcare

Our Healthcare series is for professionals working in the Healthcare industry. The course materials include examples with metrics such as pain scores, patient complaints, time, nonconformities, and patient satisfaction.

Minitab Essentials

Manufacturing

In this 2-day foundational course you will learn to minimize the time required for data analysis by using Minitab to import data, develop sound statistical approaches to exploring data, create and interpret compelling graphs, and export results. Analyze a variety of real-world data sets to learn how to align your applications with the right statistical tool and interpret statistical output to reveal problems with a process or evidence of an improvement. Learn the fundamentals of important statistical concepts, such as hypothesis testing and confidence intervals, and how to uncover and describe relationships between variables with statistical modeling tools.

This course places a strong emphasis on making sound decisions based upon the practical application of statistical techniques commonly found in manufacturing, engineering, and research and development endeavors.

Topics include:
 
  • Importing and Formatting Data
  • Bar Charts
  • Histograms
  • Boxplots
  • Pareto Charts
  • Scatterplots
  • Tables and Chi-Square Analysis
  • Measures of Location and Variation
  • t-Tests
  • Proportion Tests
  • Tests for Equal Variance
  • Power and Sample Size
  • Correlation
  • Simple Linear and Multiple Regression
  • One-Way ANOVA
  • Multi-Variable ANOVA
Prerequisites: None
Essentials
Essentials

Statistical Quality Analysis

Manufacturing

Develop the necessary skills to successfully evaluate and certify manufacturing and engineering measurement systems. Learn the fundamentals of statistical process control and how these important quality tools can provide the necessary evidence to improve and control manufacturing processes. Develop the skills to know when and where to use the various types of control charts available in Minitab for your own processes. Learn how to utilize important capability analysis tools to evaluate your processes relative to internal and customer specifications.

The course emphasis is placed on teaching quality tools as they relate to manufacturing processes.

Topics include:
 
  • Gage R&R
  • Destructive Testing
  • Gage Linearity and Bias
  • Attribute Agreement
  • Variables and Attribute Control Charts
  • Capability Analysis for Normal, Nonnormal, and Attribute Data
Prerequisites: Minitab Essentials
Essentials
Essentials

Factorial Designs

Manufacturing

Learn to generate a variety of full and fractional factorial designs using Minitab’s intuitive DOE interface. Real-world applications demonstrate how the concepts of randomization, replication, and blocking form the basis for sound experimentation practices. Develop the skills necessary to correctly analyze the resulting data to effectively and efficiently reach experimental objectives.

Use Minitab’s customizable and powerful graphical displays to interpret and communicate experimental results to improve products and processes, find critical factors that impact important response variables, reduce process variation, and expedite research and development projects.

Topics include:
 
  • Design of Factorial Experiments
  • Normal Effects Plot and Pareto of Effects
  • Power and Sample Size
  • Main Effect, Interaction, and Cube Plots
  • Center Points
  • Overlaid Contour Plots
  • Multiple Response Optimization
Prerequisites: Minitab Essentials
Factorial
Factorial

Additional Topics in Statistical Quality Analysis

Manufacturing

Continue to build on the fundamental concepts taught in the Manufacturing Statistical Quality Analysis course by learning additional tools that help to improve and control your processes. Develop the necessary skills to successfully evaluate and certify manufacturing and engineering measurement systems with multiple gages or different locations on a part. Learn how to evaluate a random sample of product from a lot to determine whether to accept or reject the entire lot. Expand your knowledge of control charting to handle rare events and time weighted data.

Learn how to utilize important capability analysis tools to evaluate your processes relative to internal and customer specifications. The course emphasis is placed on teaching quality tools as they relate to manufacturing processes.

Topics include:
 
  • Gage R&R Expanded
  • Orthogonal Regression
  • Tolerance Intervals
  • Acceptance Sampling
  • Between-Within Analysis
  • Control Charts including EWMA, Short-Run, and Rare Events
Prerequisites: Minitab Essentials, Statistical Quality Analysis
Addl Topics In SQA
Addl Topics In SQA

Analysis of Nonnormal Data for Quality

Manufacturing

Continue to build on the fundamental concepts taught in the Manufacturing Statistical Quality Analysis course by learning additional tools for measuring quality levels and assessing process capability when your data are skewed, have extreme outliers, are multimodal, or are clustered. Expand your knowledge of control charting by learning how to correctly identify special cause variation in the presence of nonnormal data.

Develop the necessary skills to successfully use graphical methods and statistical tests for detecting nonnormal data and choosing an appropriate distribution or transformation for the analysis. Learn about the impact of poor measurement resolution and sample size on normality testing.

Topics include:
 
  • Probability Plots
  • Tests for Normality
  • Capability Analysis for Nonnormal Data
  • Box-Cox and Johnson transformations
  • Multiple Variables Capability Analysis
  • Tolerance Intervals
  • Individuals Control Charts
  • Multiple Failure Modes Analysis
Prerequisites: Minitab Essentials, Statistical Quality Analysis
non normal Tol Interv course
non normal Tol Interv course

Statistical Modeling

Manufacturing

Continue to build on the fundamental statistical analysis concepts taught in the Minitab Essentials course by learning additional statistical modeling tools that help to uncover and describe relationships between variables. Hands-on examples illuminate how modeling tools help reveal key inputs and sources of variation in your processes.

Learn how to use statistical models to investigate how processes may behave under varying conditions. This course provides techniques to help you better understand your processes and to focus and verify your improvement efforts.

Topics include:
 
  • Multiple and Stepwise Regression
  • Nonlinear Regression
  • Partial Least Squares
  • Multi-Variable ANOVA with Covariates
  • Nesting and Random Factors
  • MANOVA
  • Binary and Nominal Logistic Regression
Prerequisites: Minitab Essentials
Statistical Modeling
Statistical Modeling

Response Surface Designs

Manufacturing

Expand your knowledge of basic 2 level full and fractional factorial designs to those that are ideal for process optimization. Learn how to use Minitab’s DOE interface to create response surface designs, analyze experimental results using a model that includes quadratics, and find optimal factor settings.

Learn how to experiment in the real world by using techniques such as sequential experimentation that balance the discovery of critical process information while being sensitive to the resources required to obtain that information. Learn how to find factor settings that simultaneously optimize multiple responses.

Topics include:
 
  • Central Composite and Box-Behnken Designs
  • Calculations for Steepest Ascent
  • Overlaid Contour Plots
  • Multiple Response Optimization
Prerequisites: Minitab Essentials, Factorial designs
Response Surface
Response Surface

DOE in Practice

Manufacturing

Learn how to handle common DOE scenarios where modifications to the analysis of classic factorial and response surface designs are necessary due to the nature of the response variable or the data collection process. Develop techniques for experimental situations often encountered in practice such as missing data and hard-to-change factors. Understand how to account for variables (covariates) that may affect the response but cannot be controlled in the experiment.

Explore the opportunities to minimize costs or variability while simultaneously optimizing an important product or process characteristic. Learn how to find and quantify the effect that factors have on the probability of a critical event, such as a defect, occurring.

Participants of the course will be able to:
 
  • Investigate the effect of a noise factors or covariate on the response
  • Create and run a design with hard to change factors
  • Optimize responses while minimizing cost or variability
  • Analyze a DOE with a binary response
Prerequisites: Minitab Essentials, Factorial designs
Contour Plot DOE Course
Contour Plot DOE Course

Formulation and Mixture Designs

Manufacturing

Learn the principles of designing experiments and analyzing the resulting data for processes that are comprised of the mixing and blending of ingredients such as those commonly found in the pharmaceutical, chemical, food, and consumer goods industries. By utilizing Minitab’s easy to understand interface, create experiments designed to study and uncover important process information related to mixture processes with the minimal amount of experimental resources. Learn how to interpret graphical and statistical output to understand a mixture’s blending properties and to choose the appropriate formulation needed to optimize one or more critical process characteristics.

Topics include:
 
  • Simplex Lattice and Centroid Designs
  • Upper and Lower Constraints
  • Pseudocomponents
  • Extreme Vertices Designs
  • Mixture-Process Variable designs
  • Mixture-Amount Designs
Prerequisites: Minitab Essentials, Factorial designs
Simplex Plot Formulations Course
Simplex Plot Formulations Course

Introduction to Reliability

Manufacturing

Determine lifetime characteristics of a product using both graphical and quantitative analysis methods. Examine case studies containing censored and uncensored data to learn how to correctly handle a wide variety of data structures commonly found in reliability.

Explore the common distributions used to model failure rates and understand their hazard functions to develop the necessary skills to choose the appropriate distribution. Model product reliability when product failure comes from different failure types.

Topics include:
 
  • Parametric and Nonparametric Distribution Analysis
  • Estimation and Demonstration Test Plans
  • Growth Curves
  • Multiple Failure Modes
  • Warranty Predictions
  • Weibayes Analysis
Prerequisites: Minitab Essentials
Intro Reliability
Simplex Plot Formulations Course

Advanced Reliability

Manufacturing

Study and describe the impact that explanatory variables have on product lifetime. Determine the effect of factors and covariates on product failure and the risk of failure to a population of products. Learn how to obtain reliability estimates on highly reliable products in a reasonable amount of time and assess when those components are expected to fail.

Establish appropriate sample sizes and allocation of units to stress levels for an accelerated life test and determine the effect of a stress variable on the probability of failure. A strong emphasis is placed on using appropriate probability models to predict important lifetime characteristics of your products both in test studies and in the field.

Participants of the course will be able to:
 
  • Compare reliability distributions
  • Understand the concepts and uses of regression with life data
  • Use accelerated life testing to determine the probability of product failure
Prerequisites: Minitab Essentials, Introduction to reliability
Advanced Reliability
Intro Reliability

Automating Analyses in Minitab

Manufacturing / Services

Automate your Minitab analysis and save time with macros. Learn how to use Minitab’s command syntax to write macros that instantaneously import data from a database, manipulate poorly structured Excel files, and perform statistical analysis with minimal user input. By the end of this hands-on course, you will be able to write and execute your own custom macros.

Topics include:
 
  • Command Line
  • Automating Analyses through Execs
  • Creating Macros
  • Minitab Customization
  • Control Statements
Prerequisites: Minitab Essentials
Intro Reliability

Minitab Essentials for Service Quality

Services

In this 2-day foundational course you will learn to minimize the time required for data analysis by using Minitab to import data, develop sound statistical approaches to exploring data, create and interpret compelling graphs, and export results. Analyze a variety of real world data sets to learn how to align your applications with the right statistical tool, and interpret statistical output to reveal problems with a process or evidence of an improvement. Learn the fundamentals of important statistical concepts, such as hypothesis testing and confidence intervals, and how to uncover and describe relationships between variables with statistical modeling tools.

This course places a strong emphasis on making sound decisions based upon the practical application of statistical techniques commonly used in business, transactional, and services processes.

Topics include:
 
  • Importing and Formatting Data
  • Bar Charts
  • Histograms
  • Boxplots
  • Pareto Charts
  • Scatterplots
  • Tables and Chi-Square Analysis
  • Measures of Location and Variation
  • t-Tests
  • Proportion Tests
  • Tests for Equal Variance
  • Power and Sample Size
  • Correlation
  • Simple Linear and Multiple Regression
  • One-Way ANOVA
Prerequisites: None
Essentials
Essentials

Statistical Quality Analysis for Service Quality

Services

Develop the necessary skills to successfully evaluate and certify your measurement systems. Learn the basic fundamentals of statistical process control and how these important quality tools can provide the necessary evidence to improve and control your processes. Develop the skills to know when and where to use the various types of control charts available in Minitab. Learn how to utilize important capability analysis tools to evaluate your processes relative to internal and customer specifications.

The course emphasizes the teaching of quality tools as they pertain to service industries.

Topics include:
 
  • Attribute Agreement for Binary, Nominal, and Ordinal Data
  • Kappa and Kendall’s Coefficients
  • Gage R&R
  • Variables and Attribute Control Charts
  • Capability Analysis for Normal, Nonnormal, and Attribute Data
Prerequisites: Minitab Essentials for Service Quality
Essentials
Essentials

Statistical Modeling for Service Quality

Services

Expand your set of available statistical tools by analyzing data from real world problems experienced in service industries. Strengthen analysis skills with tools used to explore and describe relationships between variables. Learn to discover and describe features in data related to the effect and impact of time, and how to forecast future process behavior.

Utilize graphical and quantitative approaches to describe similarities and differences between the effects of various factors on important quality characteristics. Learn how to find and quantify the effect that factors have on the probability of a critical event occurring.

Topics include:
 
  • Multi-Variable ANOVA
  • Binary Logistic Regression
  • Factorial Designs
  • Time Series Tools, including Forecasting
  • Seasonality and Decomposition
  • Multiple Linear Regression including Best Subsets and Stepwise Regression
Prerequisites: Minitab Essentials for Service Quality
Essentials
Essentials

Fundamentals of Analytics

Predictive Analytics

In this foundational course, you will learn to minimize the time required for data analysis by using Minitab to import data, develop sound statistical approaches to exploring data, create and interpret compelling visualizations, and export results. Automate your Minitab analysis with minimal user input to save time. Analyze a variety of real-world data sets to learn how to align your applications with the right analytics tool and interpret the statistical output. Learn the fundamentals of important statistical concepts such as hypothesis testing and confidence intervals.

This course places a strong emphasis on making sound decisions based upon the practical application of statistical techniques commonly used in business, manufacturing, and transactional processes.

Topics include:
 
  • Importing and Formatting Data
  • Exec Macros
  • Bar Charts
  • Histograms
  • Boxplots
  • Pareto Charts
  • Scatterplots
  • Measures of Location and Variation
  • t-Tests
  • Test for Equal Variance
  • Power and Sample Size
Prerequisites: None
Essentials
Essentials

Regression Modeling and Forecasting

Predictive Analytics

Continue to build on the fundamental statistical analysis concepts taught in the Fundamentals of Analytics course by learning to explore and describe relationships between variables with statistical modeling tools. Discover and describe features in data related to the effect and impact of time, and how to forecast future behavior.

Learn how to find and quantify the effect that input variables have on the probability of a critical event occurring. Hands-on examples illuminate how modeling tools help reveal key inputs and sources of variation in your data.

Topics include:
 
  • Scatterplots
  • Correlation
  • Simple Linear Regression
  • Time Series Tools, including Exponential Smoothing
  • Trend Analysis
  • Decomposition
  • Multiple and Stepwise Regression
  • Binary Logistic Regression
  • Regression with Validation
Prerequisites: Fundamentals of Analytics
Essentials
Essentials

Machine Learning

Predictive Analytics

Expand your analytics by analyzing data from real world problems experienced in many industries to explore and describe relationships between variables. Learn to use supervised machine learning techniques such as CART®  to analyze patterns found in historical data to gain better insights, identify potential risks, seek out improvement opportunities, and make predictions about the future.

Use unsupervised machine learning tools such as Clustering to detect natural partitions in the data and group observations or variables into homogenous sets. Reduce the dimensionality of data by transforming the original data into a set of uncorrelated variables.

Topics include:
 
  • Discriminant Analysis
  • Test Set Validation
  • K-fold Validation
  • CART® Classification
  • Correlation
  • CART® Regression
  • Cluster Analysis
Prerequisites: Fundamentals of Analytics, Regression Modeling and Forecasting
Essentials
Essentials

Minitab Essentials for Medical Devices

Medical Devices

In this 2-day foundational course you will learn to minimize the time required for data analysis by using Minitab to import data, develop sound statistical approaches to exploring data, create and interpret compelling graphs, and export results. Analyze a variety of real-world medical device data sets to learn how to align your applications with the right statistical tool and interpret statistical output to reveal problems with a process or evidence of an improvement. Learn the fundamentals of important statistical concepts, such as hypothesis testing and confidence intervals, and how to uncover and describe relationships between variables with statistical modeling tools.

This course places a strong emphasis on making sound decisions based upon the practical application of statistical techniques commonly found in the medical device industry.

Topics include:
 
  • Importing and Formatting Data
  • Bar Charts
  • Histograms
  • Boxplots
  • Pareto Charts
  • Scatterplots
  • Tables and Chi-Square Analysis
  • Measures of Location and Variation
  • t-Tests
  • Proportion Tests
  • Tests for Equal Variance
  • Equivalence tests
  • Power and Sample Size
  • Correlation
  • Simple Linear and Multiple Regression
  • One-Way ANOVA
  • Multi-Variable ANOVA
Prerequisites: None
Essentials
Essentials

Statistical Quality Analysis for Medical Devices

Medical Devices

Develop the necessary skills to successfully evaluate and certify measurement systems. Learn the fundamentals of statistical process control and how these important quality tools can provide the necessary evidence to improve and control medical device processes. Develop the skills to know when and where to use the various types of control charts available in Minitab for your own processes. Learn how to utilize important capability analysis tools to validate your processes relative to internal and customer specifications.

The course emphasis is placed on teaching quality tools as they relate to medical device processes.

Topics include:
 
  • Gage R&R
  • Destructive Testing
  • Gage Linearity and Bias
  • Attribute Agreement
  • Variables and Attribute Control Charts
  • Capability Analysis for Normal, Nonnormal, and Attribute data
  • Acceptance Sampling
Prerequisites: Minitab Essentials for Medical Devices
Essentials
Essentials

Factorial Designs for Medical Devices

Medical Devices

Learn to generate a variety of full and fractional factorial designs using Minitab’s intuitive DOE interface. Real-world medical device applications demonstrate how the concepts of randomization, replication, and blocking form the basis for sound experimentation practices. Develop the skills necessary to correctly analyze the resulting data to effectively and efficiently reach experimental objectives.

Use Minitab’s customizable and powerful graphical displays to interpret and communicate experimental results to improve products and processes, find critical factors that impact important response variables, reduce process variation, and expedite research and development projects.

Topics include:
 
  • Design of Factorial Experiments
  • Normal Effects Plot and Pareto of Effects
  • Power and Sample Size
  • Main Effect, Interaction, and Cube Plots
  • Center Points
  • Overlaid Contour Plots
  • Multiple Response Optimization
Prerequisites: Minitab Essentials for Medical Devices
Essentials
Essentials

Minitab Essentials for Pharmaceuticals

Pharmaceuticals

In this 2-day foundational course you will learn to minimize the time required for data analysis by using Minitab to import data, develop sound statistical approaches to exploring data, create and interpret compelling graphs, and export results. Analyze a variety of real-world pharmaceutical data sets to learn how to align your applications with the right statistical tool and interpret statistical output to reveal problems with a process or evidence of an improvement. Learn the fundamentals of important statistical concepts, such as hypothesis testing and confidence intervals, and how to uncover and describe relationships between variables with statistical modeling tools.

This course places a strong emphasis on making sound decisions based upon the practical application of statistical techniques commonly found in the pharmaceutical industry.

Topics include:
 
  • Importing and Formatting Data
  • Bar Charts
  • Histograms
  • Boxplots
  • Pareto Charts
  • Scatterplots
  • Tables and Chi-Square Analysis
  • Measures of Location and Variation
  • t-Tests
  • Proportion Tests
  • Tests for Equal Variance
  • Equivalence tests
  • Power and Sample Size
  • Correlation
  • Simple Linear and Multiple Regression
  • Stability Analysis
  • One-Way ANOVA
  • Multi-Variable ANOVA
Prerequisites: None
Essentials
Essentials

Statistical Quality Analysis for Pharmaceuticals

Pharmaceuticals

Develop the necessary skills to successfully evaluate and certify measurement systems. Learn the fundamentals of statistical process control and how these important quality tools can provide the necessary evidence to improve and control pharmaceutical processes. Develop the skills to know when and where to use the various types of control charts available in Minitab for your own processes. Learn how to utilize important capability analysis tools to validate your processes relative to internal and customer specifications.

The course emphasis is placed on teaching quality tools as they relate to pharmaceutical processes.

Topics include:
 
  • Gage R&R
  • Destructive Testing
  • Gage Linearity and Bias
  • Attribute Agreement
  • Variables and Attribute Control Charts
  • Capability Analysis for Normal, Nonnormal, and Attribute data
  • Acceptance Sampling
Prerequisites: Minitab Essentials for Pharmaceuticals
Essentials
Essentials

Factorial Designs for Pharmaceuticals

Pharmaceuticals

Learn to generate a variety of full and fractional factorial designs using Minitab’s intuitive DOE interface. Real-world medical device applications demonstrate how the concepts of randomization, replication, and blocking form the basis for sound experimentation practices. Develop the skills necessary to correctly analyze the resulting data to effectively and efficiently reach experimental objectives.

Use Minitab’s customizable and powerful graphical displays to interpret and communicate experimental results to improve products and processes, find critical factors that impact important response variables, reduce process variation, and expedite research and development projects.

Topics include:
 
  • Design of Factorial Experiments
  • Normal Effects Plot and Pareto of Effects
  • Power and Sample Size
  • Main Effect, Interaction, and Cube Plots
  • Center Points
  • Overlaid Contour Plots
  • Multiple Response Optimization
Prerequisites: Minitab Essentials for Pharmaceuticals
Essentials
Essentials

Minitab Essentials for Healthcare

Healthcare

In this 2-day foundational course you will learn to minimize the time required for data analysis by using Minitab to import data, develop sound statistical approaches to exploring data, create and interpret compelling graphs, and export results. Analyze a variety of real world data sets to learn how to align your applications with the right statistical tool, and interpret statistical output to reveal problems with a process or evidence of an improvement. Learn the fundamentals of important statistical concepts, such as hypothesis testing and confidence intervals, and how to uncover and describe relationships between variables with statistical modeling tools.

This course places a strong emphasis on making sound decisions based upon the practical application of statistical techniques commonly used in healthcare.

Topics include:
 
  • Importing and Formatting Data
  • Bar Charts
  • Histograms
  • Boxplots
  • Pareto Charts
  • Scatterplots
  • Tables and Chi-Square Analysis
  • Measures of Location and Variation
  • t-Tests
  • Proportion Tests
  • Tests for Equal Variance
  • Power and Sample Size
  • Correlation
  • Simple Linear and Multiple Regression
  • One-Way ANOVA
Prerequisites: None
Essentials
Essentials

Statistical Quality Analysis for Healthcare

Healthcare

Develop the necessary skills to successfully evaluate and certify your measurement systems. Learn the basic fundamentals of statistical process control and how these important quality tools can provide the necessary evidence to improve and control your processes. Develop the skills to know when and where to use the various types of control charts available in Minitab. Learn how to utilize important capability analysis tools to evaluate your processes relative to internal and customer specifications.

The course emphasizes the teaching of quality tools as they pertain to the healthcare industry.

Topics include:
 
  • Attribute Agreement for Binary, Nominal, and Ordinal Data
  • Kappa and Kendall’s Coefficients
  • Gage R&R
  • Variables, Attribute, and Rare Event Control Charts
  • Capability Analysis for Normal, Nonnormal, and Attribute Data
Prerequisites: Minitab Essentials for Healthcare
Essentials
Essentials
clear