MINITAB 17 Statistical Quality Analysis

minitab 17,minitab 17 statistical quality analysis

August 17, 2021


Plot 14 Odeniran Close,Off Opebi Road,Opebi,Ikeja,Lagos-JK Michaels   View map


Minitab 17 statistical quality analysis training can be customized for the service or manufacturing sector.It focuses on the utilization of Minitab Statistical Software tools and features from a manufacturing, engineering and business process perspective.

The four days consist of the following topics:

Day 1 : Introduction to Minitab
Day 2 : Basic Statistics
Day 3 : Statistical Quality Analysis
Day 4 : Factorial Designs

Introduction to Minitab 17

Decrease the time required for statistical analysis by quickly learning to navigate Minitab’s user-friendly and customizable environment. Learn how to import/export data and output between Minitab and various software and database systems. Enhance your ability to create, manipulate, and restructure data. Develop sound statistical approaches to data analysis by learning how to create and interpret a wide variety of graphs and numerical measures useful for quality improvement initiatives. This Minitab 17 course focuses on the utilization of these tools as they pertain to applications commonly found in manufacturing, engineering, and business processes.

Topics covered include: Charts, Histograms, Boxplots, Dotplots, Scatterplots, Tables, Measures of Location and Variation, ODBC

This course is a prerequisite for all other general Minitab courses.

Basic Statistics

Augment your graphical analysis skills using Minitab’s powerful statistical tools. Develop the foundation for important statistical concepts such as hypothesis testing and confidence intervals. By analyzing a variety of real world data sets, learn how to match the appropriate statistical tool to your own applications and how to correctly interpret statistical output to quickly reveal problems with a process or to show evidence of an improvement. Learn how to explore critical features in your processes through statistical modeling tools that help to uncover and describe relationships between variables. A strong emphasis is placed on making good business decisions based upon the practical application of statistical techniques commonly found in manufacturing, engineering, and research and development endeavors.

Tools Covered Include: t-Tests, Proportion Tests, Tests for Equal Variance, Power and Sample Size, Correlation, Simple Linear and Multiple Regression, ANOVA and GLM

Prerequisite: Introduction to Minitab

Optional Topic for On-Site Training: Nonparametric Tests

Minitab 17 Statistical Quality Analysis

Develop the necessary skills to successfully evaluate and certify manufacturing and engineering 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 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.

Tools Covered Include: Gage R&R, Destructive Testing, Gage Linearity and Bias, Attribute Agreement, Variables and Attribute Control Charts, Capability Analysis for Normal, Non-normal and Attribute data

Prerequisites: Introduction to Minitab and Basic Statistics

Optional Topic for On-Site Training: Acceptance Sampling for Attribute and/or Variables Data

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. Develop the skills necessary to correctly analyze 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.

Tools and topics Covered 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: Introduction to Minitab and Basic Statistics

Days may be booked as a individual days (please note, per-requisites apply) or a full 3-day course.

Course Outlines


The three days consist of the following topics:

Day 1 : Introduction to Minitab
Day 2 : Basic Statistics
Day 3 : Statistical Quality Analysis
Factorial Designs

Who Should Attend?


Professional that intend to master statistical quality analysis

Course Dates