Minitab Service Quality
Level 1 Service Quality Course with Minitab
Length of training: 2 days
Day 1: Introduction to Minitab
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 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, Box plots, Dot plots, Scatter plots, Tables, Measures of Location and Variation, ODBC
Target Participants: Professionals who are working in automotive industries, chemical production plants, and other companies involved in manufacturing. The course materials include examples with metrics such as diameters, pressure, and hardness.
Day 2: 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, can 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.
Target Participants: Professionals who are working in automotive industries, chemical production plants, and other companies involved in manufacturing. The course materials include examples with metrics such as diameters, pressure, and hardness.
Level 2 Service Quality Course with Minitab
Length of training: 2 days
Day 1: 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, many enhancement in Minitab Release 15, 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, Gage Stability, Attribute Agreement, Variables and Attribute Control Charts, Capability Analysis for Normal, Non-normal and Attribute data.
Target Participants: Professionals who are working in automotive industries, chemical production plants, and other companies involved in manufacturing. The course materials include examples with metrics such as diameters, pressure, and hardness.
Day 2: Advanced Topics
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.
Tools Covered Include: Multivariate ANOVA, GLM; Binary Logistic Regression; Factorial Designs; Time Series Tools including Exponential Smoothing, Trend Analysis, Decomposition, Multiple Linear Regression including Best Subsets and Stepwise Regression.
Target participants: Professionals who are working in financial services, healthcare and other areas that use metrics such as time, defect rates, and revenue data. The course materials include more examples of analyzing categorical (count) data than continuous (measurement) data.