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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
