Customer (On-Site & Virtual) Training

MINITAB ESSENTIALS FOR SERVICE QUALITY

In this 2-day foundational course, you will learn to minimize the time required for data analysis with Minitab. We will cover how to import data into Minitab, develop sound statistical approaches to explore data, create and interpret compelling graphs, and export results. You will 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

MINITAB ESSENTIALS FOR MEDICAL DEVICES

In this 2-day foundational course, you will learn how to efficiently perform data analysis by using Minitab! With Minitab, you can import data, develop sound statistical approaches to explore data, create and interpret compelling graphs, and export results. This course teaches you how to analyze a variety of real-world medical device data sets, which will help you 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

MINITAB ESSENTIALS FOR HEALTHCARE

In this 2-day foundational course, you will learn to minimize the time required for data analysis by using Minitab. With Minitab, you will practice importing data, developing sound statistical approaches to explore data, creating and interpreting compelling graphs, and finally, exporting results. By analyzing a variety of real-world data sets, you will 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

MINITAB ESSENTIALS FOR PHARMACEUTICALS

In this 2-day foundational course, you will learn to minimize the time required for data analysis by using Minitab! With Minitab, you will practice importing data, developing sound statistical approaches to explore data, creating and interpreting compelling graphs, and finally, exporting results. Discover how to analyze a variety of real-world pharmaceutical data sets to practice aligning your applications with the right statistical tool and interpreting 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
• One-Way ANOVA
• Multi-Variable ANOVA

Prerequisites: None

STATISTICAL QUALITY ANALYSIS

In this course, you will develop the necessary skills to successfully evaluate and certify manufacturing and engineering measurement systems. Our experts will teach you the fundamentals of statistical process control and how these important quality tools can provide the necessary evidence to improve and control manufacturing processes. You will develop the skills to know when and where to use the various types of control charts available in Minitab for your own processes. And you will 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 the 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

Prerequisite: Minitab Essentials

STATISTICAL QUALITY ANALYSIS FOR SERVICE QUALITY

In this course, you will learn the fundamentals of statistical process control and how these important quality tools can provide evidence to improve and control your processes. Develop the necessary skills to successfully evaluate and certify your measurement systems. Plus, practice skills to know when and where to use the various types of control charts available in Minitab. You will understand how to utilize important capability analysis tools so you can evaluate your processes relative to internal and customer specifications.

This 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

Prerequisite: Minitab Essentials for Service Quality

STATISTICAL QUALITY ANALYSIS FOR MEDICAL DEVICES

In this course, you will 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. You will develop the skills to know when and where to use the various types of control charts available in Minitab for your own processes. Plus, 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

Prerequisite: Minitab Essentials for Medical Devices

STATISTICAL QUALITY ANALYSIS FOR HEALTHCARE

You will develop the 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 evidence to improve and control your processes. You will practice the skills for knowing 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

Prerequisite: Minitab Essentials for Healthcare

STATISTICAL QUALITY ANALYSIS FOR PHARMACEUTICALS

Get ready to develop the skills to successfully evaluate and certify measurement systems! You will learn the fundamentals of statistical process control and how these important quality tools can provide evidence to improve and control pharmaceutical processes. Practice the skills to know when and where to use the various types of control charts available in Minitab for your own processes. Plus, 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

Prerequisite: Minitab Essentials for Pharmaceuticals

FACTORIAL DESIGNS

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. You will develop the skills necessary to correctly analyze the resulting data to effectively and efficiently reach experimental objectives.

You will use Minitab’s customizable and powerful graphical displays to interpret and communicate experimental results. Then you will learn how to use those 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

Prerequisite: Minitab Essentials

FACTORIAL DESIGNS FOR 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

Prerequisite: Minitab Essentials for Medical Devices

FACTORIAL DESIGNS FOR PHARMACEUTICALS

In this course, you will learn to generate 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. You will develop the skills to correctly analyze the resulting data to effectively and efficiently reach experimental objectives.

We’ll use Minitab’s customizable graphical displays to interpret and communicate experimental results. The results can be used 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

Prerequisite: Minitab Essentials for Pharmaceuticals

ADDITIONAL TOPICS IN STATISTICAL QUALITY ANALYSIS

Continue to build on the fundamental concepts taught in the Manufacturing Statistical Quality Analysis course by learning additional tools that can help you improve and control your processes. In this course, you will 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. Plus, 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

ANALYSIS OF NONNORMAL DATA FOR QUALITY

Continue to build on the fundamental concepts taught in the Manufacturing Statistical Quality Analysis course and learn additional tools! You will develop skills to measure quality levels and assess process capability when your data is skewed, has extreme outliers, is multimodal, or is clustered. Expand your knowledge of control charting by learning how to correctly identify special cause variation in the presence of nonnormal data.

You will learn how to successfully use graphical methods and statistical tests to detect nonnormal data and choose an appropriate distribution or transformation for the analysis. Plus, understand 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

STATISTICAL MODELING

Continue to build on the fundamental statistical analysis concepts taught in the Minitab Essentials course by learning additional statistical modeling tools. The new tools will help you uncover and describe relationships between variables. Hands-on examples illustrate how modeling tools can 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 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

Prerequisite: Minitab Essentials

STATISTICAL MODELING FOR SERVICE QUALITY

Expand your set of available statistical tools by analyzing data from real-world service industry problems. You will strengthen analysis skills with tools that can be used to explore and describe relationships between variables. Plus, learn to discover and describe features in data related to the effect and impact of time, and how to forecast future process behavior.

Be prepared to utilize graphical and quantitative approaches to describe similarities and differences between the effects of various factors on important quality characteristics. You will 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

Prerequisite: Minitab Essentials for Service Quality

RESPONSE SURFACE DESIGNS

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

Learn how to experiment in the real world by using sequential experimentation, which balances the discovery of critical process information while being sensitive to the resources required to obtain that information. Additionally, 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

DOE IN PRACTICE

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. You will develop techniques for experimental situations often encountered in practice, such as missing data and hard-to-change factors. Plus, build an understanding for 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.

Topics Include:

• Investigate the effect of a noise factors or covariate on the response
• Create and run a design with hard-to-change factors
• Create and run a Screening DOE
• Optimize responses while minimizing cost or variability
• Analyze a DOE with a binary response

Prerequisites: Minitab Essentials, Factorial Designs

FORMULATION AND MIXTURE DESIGNS

Learn the principles of designing experiments and analyzing the data for processes that involve mixing and blending ingredients, such as those commonly found in the pharmaceutical, chemical, food, and consumer goods industries. By utilizing Minitab’s easy-to-understand interface, you will create experiments designed to study and uncover important process information that is related to mixture processes and has minimal experimental resources. Learn how to interpret graphical and statistical output to understand a mixture’s blending properties and 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

INTRODUCTION TO RELIABILITY

Determine lifetime characteristics of a product using 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 so you can 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

ADVANCED RELIABILITY

In this course, you will study and describe the impact that explanatory variables have on product lifetime. Learn how to determine the effect of factors and covariates on product failure and the risk of failure to a population of products.  Discover how to obtain reliability estimates on highly reliable products in a reasonable amount of time and assess when those components are expected to fail.

You will walk away knowing how to establish appropriate sample sizes and allocate the appropriate amount of units to stress levels for an accelerated life test,  then 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

REGRESSION MODELING AND FORECASTING

Ready to continue building on the fundamental statistical analysis concepts taught in the Fundamentals of Analytics? This course teaches you how to explore and describe relationships between variables with statistical modeling tools. You will discover and describe features in data related to the effect and impact of time, and how to forecast future behavior.

This course explains how to find and quantify the effect that input variables have on the probability of a critical event occurring. With hands-on examples, you’ll learn how modeling tools can 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 

Prerequisite: Fundamentals of Analytics

MACHINE LEARNING

This course will help you expand your data analysis skills with real-world problem examples to teach you how to explore and describe relationships between variables. You will learn to use supervised machine learning techniques, such as CART^®, to analyze patterns found in historical data, which can help you 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. Plus, 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

ADVANCED MACHINE LEARNING

Take your analytics to the next level by analyzing data from real world problems to explore and describe relationships between variables. CART trees provide a simple tree structure for interpreting complex relationships. However, their predictive capability can often be improved by using more powerful model, which create numerous simple models (or trees) and combine them into one final model. Learn to use advanced modeling techniques such as MARS^®, TreeNet^® and Random Forests^® to analyze patterns found in historical data to gain better insights, identify potential risks, seek out improvement opportunities, and make predictions about the future. Note: A subscription to the add-on Predictive Analytics Module is required for this course.

Topics Include:

• Validation
• CART^® Classification
• TreeNet^® Classification
• Random Forests^® Classification
• Correlation
• MARS^® Regression
• CART^® Regression
• TreeNet^® Regression
• Random Forests^® Regression
• Discover Key Predictors
• Automated Machine Learning Modeling

Prerequisites: Fundamentals of Analytics, Regression Modeling and Forecasting, Machine Learning

AUTOMATING ANALYSES IN MINITAB

Learn how to automate your Minitab analysis and save time with macros! You will discover 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—all 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

Prerequisite: Minitab Essentials

ENGAGE ESSENTIALS

In this foundational course, you will learn to effectively navigate Engage and to efficiently create and manage quality improvement projects within the solution. Develop the ability to utilize project roadmaps to insert and organize a wide variety of project tools. Interact with data on maps, brainstorming tools, and forms. Understand how data is shared throughout projects and with the dashboard.

Discover how to create ideas and manage project phase gate reviews via workflow. Access centralized reporting and view summary metrics across projects via the dashboard.

Topics include:

• Data Sharing
• Process Maps
• Value Stream Maps
• Brainstorming Tools, including Fishbones
• Forms and Analysis Captures
• Projects
• Workflow
• Dashboard

Prerequisites: None

ENGAGE CONFIGURATION

Learn to customize Engage for your organization’s specific needs via various important features within a sandbox. Discover how to build and customize project templates to align with your most-used methodologies. Develop custom tool templates for maps, brainstorming tools, and forms. Create and edit the custom data fields that drive the platform's powerful data sharing capabilities. Learn how to connect forms to your subscription's data fields, enabling this data sharing inside individual projects and with the dashboard.

Understand how project data rolls up to the dashboard and create custom dashboard reports utilizing filters, summaries, and column sets. Establish workflow settings, configuring steering committees to vet idea proposals and review boards to manage phase gate reviews of active projects.

Topics include:

• Engage Sandbox
• Project Templates
• Tool Templates
• Form Templates
• Data Fields and Data Sharing
• Controls
• Data-Entry Tables
• Dashboard Configuration
• Workflow Configuration
• Email Notifications

Prerequisites: Engage Essentials

MONTE CARLO SIMULATION

In this course you will be introduced to the concepts and methodology of Monte Carlo Simulation – a quantitative analysis that accounts for the risk and uncertainty of a system. Whether the system is a new product, a manufacturing line, finance activities, project work, etc., Monte Carlo Simulation allows you to fully explore the variability in an output by including the variability in the inputs.

Develop the skills to understand inputs to a model as distributions instead of constant values to answer questions such as: How does the input variation affect the response variation? Given the variation in inputs, how truly capable is the process? Which inputs transmit the most variation to the responses? Learn how to utilize Monte Carlo Simulation to model the behavior of a system. 

Topics include:

• Monte Carlo concepts and applications
• Probability distributions
• Linear models
• Response Optimizer using Minitab
• Monte Carlo simulation using Minitab Workspace
• Sensitivity Analysis
• Parameter Optimization

Prerequisites: Minitab Essentials, Factorial Designs

Data Analytics Certification

Expand your capabilities by learning about data visualizations and basic statistics and get certified in data analytics! In this certification course you will learn to develop proven analytical 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 output to reveal problems with a process or evidence of an improvement. Learn the fundamentals of important analytical concepts, such as hypothesis testing and confidence intervals, and how to uncover and describe relationships between variables with statistical modeling tools.