Six Sigma using Minitab 21 - for Beginners to Green Belts.
Level up your career by getting to the Green Belt level in Six Sigma Statistics and learn how to run Green Belt Projects
Six Sigma using Minitab 21 - for Beginners to Green Belts. free download
Level up your career by getting to the Green Belt level in Six Sigma Statistics and learn how to run Green Belt Projects
Are you ready to embark on a rewarding career path? Look no further than Six Sigma. Six Sigma has evolved into a powerhouse methodology embraced by industry titans such as Amazon, General Electric, Google, and 3M and many more. Its proven track record in optimizing business processes has led to widespread adoption across diverse sectors including finance, hospitality, and healthcare. The demand for Six Sigma professionals is skyrocketing, making it an excellent career choice.
We recognise that Six Sigma Beginners and Green belts need more support to understand the complex statistical techniques used within Six Sigma, and this has to be delivered effectively. In this course, the author uses his experience of industrial process improvement and Minitab training to provide candidates with the opportunity to really start understanding Six Sigma and get to the Green Belt Level.
Key Features of this course are:
· It covers all main topics used by Six Sigma Green Belts in easy to understand language.
· Improved and updated for Minitab 21.
· The main Six Sigma tools are explained. We use example-based learning with Quiz Quizzes and exercises to embed the learning.
· The course mainly uses the Assistant and teaches features such as Sequential DOE and Multiple Regression, the Graph Builder.
· Examples cover both continuous and attribute data where possible.
The full contents of the course are given below
1) INTRODUCTION
2) Minitab Boot CAMP
2.1 The Initial layout.
2.2 Working Alongside the Text.
2.3 Opening a File.
2.4 Importing Data from an Excel Spreadsheet.
2.5 Navigating within the Main Window.
2.6 Column Formats.
2.7 Sending Minitab Outputs to Microsoft Office Programs
2.8 Creating a Report within Minitab
3) data manipulation
3.1 Introduction to Data Manipulation
3.2 Split a Worksheet
3.3 Using Recode
3.4 Subsetting the Worksheet
3.5 Extract numeric data from a cell with Date/Time format
3.6 Using the calculator
3.7 Assigning a Function
3.8 Setting the Decimal Places & Rounding Values
3.9 Deleting data
3.10 Conditional Formatting
3.11 Using the Command Line to Execute Historical Commands
4) BUILDING GRAPHS
4.1 Introduction to Building Graphs
Part 1 The Graph Builder
4.2 Introduction to the Graph Builder
4.3 Histograms with the Graph Builder
4.4 Scatterplots with the Graph Builder
4.5 Time Series Plot with the Graph Builder
4.6 Probability Plot with the Graph Builder
Part 2 Graphical Analysis with the Assistant
4.7 Introduction to Graphical Analysis with the Assistant
4.8 Main Effects Plot
4.9 Main Effects Screener
4.10 Scatterplot Screener
Part 3 Producing Graphs with the Traditional Menu’s
4.11 Boxplots and the Menu System
4.12 Editing Graphs
4.13 Duplicating Graphs
4.14 The Individual Value plot
4.15 The Dot plot
4.16 The Bar Chart
4.17 Changing the Order on a Categorical Axis
4.18 The Time Series Plot
4.19 The Bubble Plot
4.20 The Pareto Plot
4.21 The Scatter plots
4.22 The Marginal Plot
4.23 The Parallel Co-ordinate Plot
Part4 Minitab 20’s New Graphs
4.24 The Heat Map
4.25 The Binned Scatter Plot
5) Core Statistics
5.1 Introduction.
5.2 Types of Data
5.3 Measuring the Centre of a Data Sample
5.4 Measuring the Variation of a Data Sample
5.5 Populations and Samples
5.6 Confidence Intervals
5.7 The Normal Distribution
5.8 The Central Limit Theorem
6) An Overview of Hypothesis Testing
6.1 What is Hypothesis Testing.
6.2 Understanding the Procedure
7) Hypothesis Testing
7.1 Introduction to Hypothesis Testing.
Tests Comparing One Sample to a Target
7.2 1 Sample T
7.3 1 Sample StDev
7.4 1 Sample % Defective
7.5 Chi-Square Goodness of Fit
Tests Comparing Two Samples with Each Other
7.6 2 Sample T
7.7 Paired T
7.8 2 Sample StDev
Tests Capable of Comparing more than Two Samples
7.9 Chi-Square % Defective
7.10 Chi-Square Test for Association
7.11 Hypothesis Testing Exercises
8) ANOVA
8.1 Introduction to ANOVA
8.2 The theory behind ANOVA
8.3 One-Way ANOVA
8.4 StDev Test using the Assistant
8.5 ANOVA General Liner model (GLM)
8.6 GLM examples
8.7 ANOVA Exercises
9) Control charts
9.1 Introduction to Control Charts
9.2 False Alarms
9.3 Subgrouping
9.4 Subgroup Size and Sampling Frequency
9.5 Detection Rules used for Special Cause Variation
9.6 Control Chart Selection for Continuous Data
9.7 I-MR Chart
9.8 Xbar-R Chart
9.9 Xbar-S Chart
9.10 Control Charts for Attribute Data
9.11 Control Chart Exercise
10) Process Capability
10.1 Simple Process Yield Metrics
10.2 Introduction to Process Capability
10.3 Basic Process Capability.
10.4 Z Scores
10.5 Sigma Shift
10.6 Off-Centre Distributions
10.7 Overall Capability and Within Capability
10.8 Normality
10.9 Summary of Process Capability
10.10 Process Capability for Continuous Data
10.11 Process Capability for Attribute Data
10.12 Process Capability Exercises
11) Evaluation of Measurement Systems
11.1 What is Measurement System Analysis (MSA)
11.2 Why MSA fundamental to DMAIC
11.3 When to Apply MSA
11.4 What we Cover
11.5 Types of Measurement Error
11.6 Accuracy Errors
11.7 Precision Errors
11.8 A Breakdown of Measurement Errors
11.9 Gage R&R Introduction
11.10 Gage R&R Crossed
11.11 Attribute Agreement Analysis within the Assistant
11.12 MSA Exercises
12) Regression
12.1 What is Regression?
12.2 What are we covering?
12.3 Simple Regression
12.4 Introduction to Multiple Regression
12.5 Multi-Collinearity and Variance Inflation Factors
12.6 Multiple Regression using the Assistant
12.7 Regression Exercises
13) Design of Experiments
13.1 What is Design of Experiments
13.2 DOE Terminology
13.3 The DOE flowchart in the Assistant
13.4 DOE Considerations
13.5 Sequential DOE Bacterial Growth Example
13.6 Sequential DOE Fuel Efficiency Example
13.7 Sequential DOE Exercise
14) Improvement Methodology
14.1 Improvement Methodology Part 1
14.2 Improvement Methodology Part 2
