Course Outline
Introduction
Six Sigma Overview
- Lean Six Sigma vs Six Sigma
- Management System
- Maturity Continuum
Six Sigma Phases
- Define phase
- Measure phase
- Analyze phase
- Improve phase
- Control phase
Statistical Analysis Basics in Minitab
- Descriptive statistics
- Inferential statistics
- Data Types
Preparing the Development Environment
- Installing and configuring Minitab
Graphs and Statistics
- Creating graphs with plots and charts
- Working with descriptive statistics
Probability and Process Capability
- Defining probability
- Using distributions
- Calculating process capability
- Processing performance
Correlation Regression and Hypothesis Testing
- Creating an appropriate diagram
- Calculating correlation coefficients
- Performing Z tests and t-tests
Summary and Conclusion
Requirements
- A basic understanding of computers
Audience
- Data Analysts
Testimonials (7)
The subject matter and the pace were perfect.
Tim - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course - Programming with Big Data in R
The pace was just right and the relaxed atmosphere made candidates feel at ease to ask questions.
Rhian Hughes - Public Health Wales NHS Trust
Course - Introduction to Data Visualization with Tidyverse and R
We were using road accident data for practicals
Maphahamiso Ralienyane - Road Safety Department
Course - Statistical Analysis using SPSS
Well thought out and high grade planning materials.
Andrew - Office of Projects Victoria - Department of Treasury & Finance
Course - Forecasting with R
Wasn't boring, the trainer could keep the attention, the topics were covered in depth.
Marta - Ministerstwo Zdrowia
Course - Advanced R Programming
Very tailored to needs.
Yashan Wang
Course - Data Mining with R
At the end of the class, we had a great overview of the language, we were provided tools to continue learning and were provided suggestions on how to continue learning. We covered AI/ML information.