Lean Six Sigma Green Belt Training Presentation

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• Lean Six Sigma Green Belt Training Presentation – 2501 Slides
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➡️ You Will Learn Below Things in This Presentation

➡️ UNIT 1: Introduction to Six Sigma

• Chapter 1: What is Six Sigma?
• Chapter 2: Six Sigma History and Application
• Chapter 3: Process Improvement & Quality Methods
• Chapter 4: Lean Concepts
• Chapter 5: Basic Six Sigma Concepts
• Chapter 6: Approaching the Problem

➡️ Unit 2: Projects and Processes

• Chapter 7: What is a Process?
• Chapter 8: Quality
• Chapter 9: Selecting the Right Projects
• Chapter 10: Basic Six Sigma Team Management
• Chapter 11: Introduction to DMAIC and DMADV

➡️ Unit 3: Advanced DMAIC

• Chapter 12: Define
• Chapter 13: Measure
• Chapter 14: Analyze
• Chapter 15: Improve
• Chapter 16: Control

➡️ Unit 4: Beginner Statistics

• Chapter 17: Intermediate Graphical Analysis
• Chapter 18: Normal Probability Distributions
• Chapter 19: Correlation and Regression

➡️ Unit 5: Intermediate Statistics

• Chapter 20: Non-Normal Probability Distributions
• Chapter 21: Hypothesis Testing
• Chapter 22: Sample Size
• Chapter 23: Advanced Control Charts
• Chapter 24: Applying Statistics to Business Applications through Six Sigma

➡️ Unit 6: Advanced Control

• Chapter 25: Introduction to Minitab
• Chapter 26: Graphs and Quality Tools in Minitab
• Chapter 27: The Stat Menu in Minitab

➡️ LEAN SIX SIGMA APPLICATIONS & CASE STUDY

➡️ LEAN SIX SIGMA EXCEL TEMPLATES

➡️ Unit 1: Introduction to Six Sigma 

➡️ Chapter 1: What is Six Sigma?

• What is the Six Sigma Methodology?
• Quality: OLD Belief vs NEW Belief – Cost vs Quality
• Different Approaches of Six Sigma
• Six Sigma as a Symbol
• Six Sigma as a Value
• Six Sigma as a Measure
• Six Sigma as a Benchmark
• Six Sigma as a Method
• Six Sigma as a Philosophy
• Six Sigma as a Tool
• Why is it Six Sigma?
• The Goal of a Six Sigma Methodology
• Data Driven Processes and Decisions
• Decision Making Without Six Sigma
• What is beta testing?
• Decision Making with Six Sigma
• Defining 6σ
• Real World Examples
• Calculating Sigma Level
• Sigma Level Is Not a Final Indicator
• Sigma Level vs DPMO vs Yield %
• How Good is Good Enough?
• 3-Sigma Process vs 6-Sigma Process
• Common Six Sigma Principles
• Customer-Focused Improvement
• Continuous Process Improvement
• Variation
• Removing Waste
• Equipping People
• Controlling the Process
• Challenges of Six Sigma

➡️ Chapter 2: Six Sigma History and Application

• Six Sigma History and Application
• Milestones of Six Sigma
• Lean Concept
• Six Sigma Concept
• How Lean Six Sigma Concept was Born?
• What is Lean Six Sigma?
• Key Principles of Lean Six Sigma
• Benefits of Lean Six Sigma
• The Development of Statistical Process Control
• Continuous Process Improvement: Toyota and Lean
• What is Jidoka?
• Motorola’s Focus on Defects
• ABB, Allied Signal, and General Electric
• Continued Growth of Six Sigma
• Applying Six Sigma Knowledge
• Six Sigma Roles and Responsibilities
• Executive Leadership
• Champion or Sponsor
• Process Owner
• Master Black Belt
• Black Belt
• Green Belt
• Yellow Belt
• White Belt
• Certification Exams

➡️ Chapter 3: Other Process Improvement and Quality Methods

• Other Process Improvement and Quality Methods
• Other Formal Quality or Process Improvement Programs
• Lean Process Management
• Total Quality Management
• Business Process Reengineering
• Rummler-Brache
• Scrum
• The Customer Experience Management Method (CEM)
• Jump Start
• When to Use Six Sigma?

➡️ Chapter 4: Lean Concepts

• Lean Concepts
• What is Lean?
• Goals of Lean
• Benefits of Lean
• Five Principles of Lean
• The Eight Muda
• Transportation Waste
• Inventory Waste
• Motion Waste
• Waiting Waste
• Over Processing Waste
• Over Production Waste
• Defects Waste
• Not Utilizing talent Waste
• Other Forms of Waste
• Two Types of Muda
• Type I Muda
• Type II Muda
• 5S Methodology
• Phase 1: Sort
• Phase 2: Straighten (Set in order)
• Phase 3: Shine
• Phase 4: Standardize
• Phase 5: Sustain
• Benefits of 5S Method Implementation
• Just-in-Time Manufacturing
• Poka-Yoke
• Different Examples of Poka-Yoke
• Steps of Poka-Yoke Implementation
• Different Types of Poka-Yokes
• Control Poka-Yoke
• Warning Poka-Yoke
• Contact method Poka-Yoke
• Fixed value method Poka-Yoke
• Motion-step method Poka-Yoke
• Six Poka-Yoke Techniques for Error Proofing
• Takt Time Formula and Example
• TRIZ – The Theory of Inventive Problem Solving
• 40 TRIZ Principles
• Kanban
• Toyota's Six Rules of Kanban
• Example of Three Bin Kanban System
• Electronic Kanban System
• 6 Core Practices of the Kanban Method
• Rules of Kanban
• Cellular Manufacturing
• Examples of Cellular Manufacturing
• Implementation of Cellular Manufacturing

➡️ Chapter 5: Basic Six Sigma Concepts

• Basic Six Sigma Concepts
• Standard Deviation
• Calculating Standard Deviation for Population Data
• Calculating Standard Deviation with Sample Data
• Why Calculate Standard Deviation?
• The Pareto Principle
• Use of Pareto Charts
• Voice of the Customer
• Four steps to understand our customer
• What is a customer?
• Tools for Analyzing VOCs
• Kano Model
• Affinity Diagram
• Building a VOC Campaign
• General Feedback
• Specific Feedback
• Selecting the Right VOC Tools
• The Likert Scale
• Basic Metrics
• Defects
• Defect vs Defectives
• Defects per million opportunities (DPMO)
• Defects per unit (DPU)
• First Time Yield (FTY)
• Example of First Pass Yield (FPY)
• Rolled Throughput yield (RTY)
• Example of Rolled Throughput Yield (RTY)

➡️ Chapter 6: Approaching the Problem

• Approaching the Problem
• Problem-Solving Strategy in Six Sigma Project
• Example of Problem-Solving Strategy
• Where to Focus During the Six Sigma Project?
• Characteristics for Successful Six Sigma Projects
• Foundation of Six Sigma Project
• Problem Functions: y = f(x)
• The 5 Whys
• When to Use 5 Whys?
• Conducting a 5 Whys Session
• Creating a Problem Statement
• Example of a Strong Problem Statement
• Example of a Weak Problem Statement
• Writing Your Own Problem Statement
• Scope and Scope Creep

➡️ UNIT 2: PROJECTS AND PROCESSES

➡️ Chapter 7: What is a Process?

• Projects and Processes
• What is a Process?
• Different Examples of Processes
• Four Layers of the Process Definition
• The Steps
• Processing Time
• Interdependencies
• Resources and Assignment
• Major Process Components
• Inputs
• Outputs
• Events
• Tasks
• Decisions
• Process Owners
• Data
• Defining Process Components: The SIPOC
• Benefits of a SIPOC Diagram
• Creating a SIPOC Diagram
• Tips for a SIPOC Brainstorming Session
• Sample SIPOC Diagrams
• Business-Level SIPOC Diagram
• SIPOC of an Automated Process
• SIPOC with Enablers Noted
• Create Your Own SIPOC Diagram

➡️ Chapter 8: Quality

• What is Quality?
• Critical to Quality Characteristics
• Examples of Product CTQ’s
• Examples of Service CTQ’s
• Developing CTQ’s
• Why Identify CTQs?
• Using a CTQ Tree to Convert Customer Needs to Quality Metrics
• Identify Critical-to-Customer Needs
• Identify Drivers of Quality
• List Requirements for Each Driver
• The CoQ and the CoPQ
• The Cost of Poor Quality
• Calculating the Cost of Poor Quality
• The Cost of Quality
• Calculating the Cost of Quality
• The Cost of Quality and Six Sigma
• Sigma Level vs Cost of Quality as a % of Sales
• COPQ - ICEBERG
• Managing Cost of Quality
• COPQ and Lean
• The 8 Lean Wastes
• Examples of COPQ – Hard Savings
• Examples of COPQ – Soft Savings
• Quality is Critical to Success

➡️ Chapter 9: Selecting the Right Projects

• Selecting the Right Projects
• Juggling the Right Amount of Projects
• Enterprise-Level Selection Process
• Five Steps procedure for identifying Six Sigma projects
• Data-Based Review of Current State of the Organization
• Brainstorm and Describe Potential Projects
• Apply Some Basic Criteria to Shorten the List
• Create Unique Business Criteria
• Use Business Criteria to Prioritize Project Lists
• The Project Viability Model
• Project Selection at a Process Level

➡️ Chapter 10: Basic Six Sigma Team Management

• Basic Six Sigma Team Management
• Building a Six Sigma Team
• Three Types of Team Members
• Tips for Selecting Team Members
• Team Member Roles
• Sponsors and Champions
• Business or Process Owners
• Six Sigma Leaders
• Project Managers
• Timekeeper
• Scribes or Minute-Takers
• Team Members
• Timelines, Scheduling, and Milestones
• Phase-Based Timeline
• Critical Path Method
• Creating a Critical Path Diagram
• Milestone Meetings
• Budgets
• Defined Measures of Success

➡️ Chapter 11: Introduction to DMAIC and DMADV

• Introduction to DMAIC and DMADV
• DMAIC vs DMADV
• What is Change Management?
• Phase 1: Define
• Phase 2: Measure
• Phase 3: Analyze
• Phase 4: Improve or Design
• Phase 5: Control or Verify
• Which Methodology Would You Use?
• DMAIC Methodology vs DMADV Methodology
• Define
• Measure
• Analyze
• Improve
• Control
• Design
• Verify
• Breaking up the Elephant

➡️ UNIT 3: ADVANCED DMAIC

➡️ Chapter 12: Define

• Define
• Goals of Define Phase
• Project Selection
• Approaches to Project Selection:
• Project Selection – Core Components:
• Business Case
• Project Charter
• Benefits Analysis
• Project Responsibility vs Resource vs Frequency of Update:
• Creating a Project Charter
• Minimally, team charters should include
• Benefits of an Organizational Team Charter Template
• Details for Charter Elements
• Key Elements of Project Charter
• Details for Charter Elements
• Example of Project Charter
• Tips for Preparing an Effective Project Charter
• Project Ground Rules
• Define Toolset
• Stakeholder Analysis
• In and Out of the Box Method
• Is/Is Not Matrix
• Team Charter Template

➡️ Chapter 13: Measure

• Measure
• Activities of the Measure Phase
• Failure Modes and Effect Analysis
• What is FMEA?
• History of FMEA
• When to Do Failure Mode and Effects Analysis?
• Review and/or Updating of the FMEA
• Who Does an FMEA (Failure Mode and Effects Analysis)?
• Four Common Classes of FMEA
• Benefits of FMEA (Failure Mode and Effects Analysis)
• Severity in FMEA
• Severity Table
• Occurrence in FMEA
• Occurrence Table
• Detection in FMEA
• Detection Table
• RPN Number (Risk Priority Number) in FMEA
• Example of RPN Number
• What is PFMEA or Process FMEA?
• 10 Simple steps for making PFMEA
• Types of Data
• Classification of Data
• Discrete Data
• Discrete (Count) Data
• Example of Discrete Data
• Continuous Data
• Example of Continuous Data
• Collecting Data
• Manufacturing Example to understand short-term vs. long-term data
• Choosing Between Discrete and Continuous Data
• Levels of Data
• Nominal Data
• Ordinal Data
• Interval Data
• Ratio Data
• Measurement System Analysis (MSA)
• Purpose of Measurement
• Accuracy and Precision
• Example - Accuracy and Precision
• Uses of MSA
• Why to Use MSA?
• SWIPE Concept in MSA
• Variation in Measurement System
• Classification of Variation in Measurement System
• Repeatability
• Reproducibility
• Bias in Measurement System Analysis
• Linearity in Measurement System Analysis
• Stability in Measurement System Analysis
• Types of MSA (Measurement System Analysis)
• Five Parameters of GRR (Gauge R&R) Study
• Equipment Variation (EV)
• Appraiser Variation (AV)
• Gauge Repeatability & Reproducibility (Gauge R&R)
• Part Variation (PV)
• Total Variation (TV)
• Six Steps for GRR Study
• Interpreting the GRR Study Results
• NDC Value in Gauge R&R Study
• Reason of Poor Measurement System
• Improvement Points in Gauge R&R study
• Attribute MSA Study
• Attribute MSA Purpose
• Collecting Data
• Choosing the Best Measurement Systems
• Creating Accuracy
• Addressing Resolution
• Adjusting for Errors of Linearity
• Stability
• Gage R&R
• Attribute Gage R&R
• Attribute Gage R&R Data Collection
• Variable Gage R&R
• What is Population?
• What is a Sample?
• How Population and Sample are Used in Statistical Inference
• Examples of Using Population and Sample Data
• Collecting Data Samples
• Simple Random Sampling
• Stratified Sampling
• Sequential Sampling
• Samples that are not Random
• Delivering a Baseline Metric
• Baseline Performance
• Delivering a Baseline Metric
• Run Charts
• Create Basic Run Charts in Excel
• Measure Tollgate Checklist

➡️ Chapter 14: Analyze

• Analyze
• Root Cause Analysis
• Cause and Effect or Fishbone, Diagram
• 6M concepts in Manufacturing
• 8P concept in Marketing
• 4S concept in Service Industry
• Cause and Effect Diagram With Detailed Sub Causes
• When We Can Use the Fishbone or Ishikawa
• 6M Category Wise Questions for Cause-and-Effect Diagram
• Classifying the Cause-and-Effect
• Cause and Effect Brainstorm Example
• Example of Fishbone Diagram
• Five Why Analysis
• Why problem analysis is required?
• What is the problem, cause, root cause, and countermeasure?
• Key points of Why-why Analysis
• How to perform Why-why analysis?
• Idea of countermeasure
• Example of Five Why Analysis
• Root Cause Verification Matrix
• Graphical Analysis
• Graphical Concepts
• The characteristics of a good graph include
• Pareto Chart
• What is Pareto Principle?
• 5-Steps in Making Pareto Chart
• Control Impact Matrix
• What is a Control - Impact Matrix?
• When to use a Control - Impact Matrix?
• How to make a Control - Impact Matrix?
• Variations in Control Impact Matrix
• Effort - Benefit matrix / Cost-Benefit Matrix
• Prioritization Matrix
• Complex Prioritization Matrix Example
• Box Plots
• Box Plot Structure
• Dot Plot
• Time Series Plot
• Statistical Analysis
• Purpose of Basic Statistics
• Statistical Notation – Cheat Sheet
• Statistics Overview
• The purpose of sampling
• Hypothesis Testing
• Correlation and Regression Analysis
• When Correlation and Linear Regression are Used?
• Correlation Analysis
• Correlation Coefficient
• Scatter Diagram
• Different Names of Scatter Diagram
• Different uses of Scatter Diagram
• Examples of Relation Between Two Variables
• How to make a Scatter Diagram?
• Interpretation of Scatter Chart
• What is Correlation?
• Types of Correlation in Scatter Diagram
• Different possible correlation between two variables
• Perfect Positive Correlation
• Perfect Negative Correlation
• No Correlation
• Examples of Different Correlation Between Two Variables
• Tips For Using Scatter Diagrams Effectively
• Limitations of Correlation
• Regression Analysis
• Prediction Equations
• What is Regression Analysis?
• Formula of Simple Linear Regression Analysis
• How to Interpret Regression Analysis?
• Real-life Examples of Regression Analysis
• Different Types of Regression Analysis
• Difference Between Regression and Correlation
• Designing Experiments
• Reasons for Experiments
• Desired Results of Experiments
• DOE Models vs. Physical Models
• Definition for Design of Experiments
• Design of Experiments
• Basic Flow for Design of Experiments
• Factors in an Experiment
• Different Factors in an Experiment
• Design of Experiments Terminology
• How to Apply Design of Experiments?
• Selecting the Factors
• Setting the Levels
• Evaluating the Response
• 5 Phases of Design of Experiments (DoE)
• Planning
• Screening
• Modelling
• Optimizing
• Verifying
• Items to Avoid When Conducting a Designed Experiment
• Common Cause Variation Vs. Special Cause Variation
• Special Cause Variation
• Characteristics of Special Cause Variation
• Examples of Special Cause Variation
• Common Cause Variation
• Characteristics of Common Causes Variation
• Examples of Common Causes Variation
• Mission During the Lean Six Sigma Project
• Central Limit Theorem
• Practical Example – Central Limit Theorem
• Analyze Tollgate Checklist

➡️ Chapter 15: Improve

• Improve
• Selecting Solutions
• Selecting improvements to implement
• Improvement Impact Considerations
• Time frame of improvements
• Effectiveness of the improvement types
• Improvement Cost Considerations
• Initial cost to implement improvement
• Time to implement improvement
• Improvement Selection Matrix
• Example of Improvement Selection Matrix
• Solutions Selection Matrix
• An example solutions selection matrix
• Proposed Solution
• Matrix Diagram
• When to Use Matrix Diagram
• Different types of Matrix Diagrams
• How to Select the Matrix Diagram Type?
• 6 Steps for Making a Matrix Diagram
• Cost Benefit Analysis
• Net Present Value (NPV)
• Benefit-Cost Ratio (BCR)
• Six Steps of Cost Benefit Analysis
• Principles of Cost-Benefit Analysis
• Importance of Cost-Benefit analysis
• Payback, or Pay Off, Analysis
• Identify Solutions
• Implementing Solutions
• Piloting a Solution
• Analyze Pilot and Test Results
• Organizing the Project/Process Completion
• Process Decision Program Charts (PDPC)
• When We Can Use a PDPC Chart?
• How to Make a PDPC Chart?
• Example of PDPC Chart
• Tree Diagram
• When to Use the Tree Diagram?
• How to Make a Tree Diagram?
• Example of Tree Diagram as Root Cause Analysis Tool
• Pilot Plan
• Planning Implementation
• Implementation Plan
• Five categories of fool-proof plan
• The Work Plan
• Resource Plan
• Stakeholder Management Plan
• Risk Assessment Plan
• Quality Control Plan
• Documentation
• Training
• Transition
• Improve Tollgate Checklist

➡️ Chapter 16: Control

• Control
• Four techniques used for process control plans
• The key elements of a full-scale implementation plan
• Goals of Control Phase
• Lean Controls
• The Vision of Lean Supporting Your Project
• What is Waste (MUDA)?
• 7 Basic Elements of Waste (Muda In Japanese)
• The Goal of Lean Control
• 5S - Workplace Organization
• The Visual Factory
• What is Standardized Work?
• What is Kaizen?
• What is Kanban?
• Revise FMEA
• Control Plan
• Who Should Create a Control Plan?
• Reasons for control plan requirement
• Control Plan Information
• Control Plan Example
• Training Plan
• Who/What organizations require training?
• Documentation Plan
• Monitoring Plan
• Response Plan
• Response Plan – Abnormality Report
• Create a Control Plan
• Common elements of a control plan
• Control Plans Overview
• Visual Management
• Statistical Process Control
• Purpose of Statistical Process Control
• Collecting Data
• SPC Charts
• Elements of Control Charts
• Understanding the Power of SPC
• Steps for Constructing Control Charts
• Focus of Six Sigma and the Use of SPC
• Control Chart Framework
• Control and Out of Control
• Size of Subgroups
• The Impact of Variation
• Frequency of Sampling
• Control Chart Selection Process
• Different Types of Control Charts Based on Continuous Data
• Different Types of Control Charts Based on Discrete Data (Count)
• Classification of Control Charts
• Understanding Variable Control Chart Selection
• Average & Range or S (X-Bar and R or X-Bar and S)
• Individua l and Moving Range
• Pre-Control
• Exponentially Weighted Moving Average
• Cumulative Sum
• P-Chart
• nP-Chart
• C-Chart
• U-Chart
• Understanding Variable Control Chart Selection
• Detection of Assignable Causes or Patterns
• Recommended Special Cause Detection Rules
• Chart Center Line and Control Limit Calculations
• Pre-Control Charts
• Process Setup and Restart with Pre-Control
• Qualifying Process
• Monitoring Ongoing Process
• I-MR Chart
• X-Bar-R Chart
• U Chart
• Procedure for U Chart
• P Chart
• Procedure for P Chart
• Statistical Process Control Tests: Control Charts
• Interpretation of Control Chart
• Control Versus Capability
• Sigma Level
• Process Capability
• Capability as a Statistical Problem
• Capability Analysis
• Process Output Categories
• Problem Solving Options – Shift the Mean
• Problem Solving Options – Reduce Variation
• Problem Solving Options – Shift Mean & Reduce Variation
• Components of Variation
• Stability of Process
• Capability Studies
• Steps to Capability Study
• Verifying the Specifications
• Measures of Capability
• Measures of Process Capability
• Attribute Capability Steps
• Z-Score Introduction
• Z-Scores vs Standard Deviation
• Interpretation of Z-Score with Example
• Defect Prevention and Control
• Sigma Level for Project Sustaining in Control
• 6-Sigma Product/Process Design
• 5 – 6-Sigma Full Automation System for Defect Control
• Full Automation System Example
• 4 – 5-Sigma Process Interruption for Defect Control
• Process Interruption
• 3 – 5-Sigma Mistake Proofing for Defect Controls
• Traditional Quality vs Mistake Proofing
• Styles of Mistake Proofing
• Mistake Proofing Devices Design
• Types of Mistake Proof Devices
• Contact Method
• Fixed Value Method
• Motion-Step Method
• Mistake Proofing Examples
• Advantages of Mistake Proofing as a Control Method
• Defect Prevention Culture and Good Control Plans
• Control Methods/Effectiveness
• Type 1 Corrective Action = Countermeasure
• Type 2 Corrective Action = Flag
• Type 3 Corrective Action = Inspection
• End of Control and Our Objectives
• Aligning Systems and Structures
• Organizational Change
• Team Celebration and Reflection
• Control Tollgate Checklist

➡️UNIT 4: BEGINNER STATISTICS

➡️ Chapter 17: Intermediate Graphical Analysis

• Intermediate Graphical Analysis
• Additional Graphical Analysis Tools
• Bar Charts
• Create a Bar Chart in Excel
• Column versus Bar
• 3-D Bar and Column Charts
• Stacked Bar Charts
• Create a Stacked Bar Chart
• Pie Charts
• Benefits of pie charts
• X Y Scatter Diagrams
• Create a Scatter Diagram in Excel
• Creating an X-Bar Control Chart without Statistical Software
• Exercise
• Adding Free Data Analysis Tools to Excel

➡️ Chapter 18: Normal Probability Distributions

• Normal Probability Distributions
• Descriptive Statistics
• Measures of Location (central tendency)
• Measures of Variation (dispersion)
• Measures of Central Tendency
• Example of Central Tendency
• Mean (x̅ or μ)
• Median(M)
• Mode(Z)
• Measures of Location (Variation/dispersion):
• Range
• Interquartile Range
• Standard deviation
• Variance
• Inferential Statistics
• Two main types of inferential statistics
• Hypothesis testing
• Regression analysis
• Different Sampling Methods
• Inferential Statistics Examples
• Inferential Statistics vs Descriptive Statistics
• 5 Step Approach to Inferential Statistics
• Confidence Interval
• Different other tests are used in inferential statistics
• Probability Distributions
• DICE Example for Understanding Probability
• Basic Probability Practice
• Applying Basic Probability Concepts to Six Sigma Analysis
• Histograms
• Creating a Histogram in Excel
• Interpretation of the Histogram
• Normal Distribution
• Skewed Distribution
• Double Peaked / Bimodal
• Multi-Peaked / Multimodal
• Edge Peaked
• Truncated or Heart-cut
• Normal Distributions
• Characteristics of a Normal distribution
• Important properties of the normal distribution
• Empirical Rule
• Why Assess Normality?
• Tools for Assessing Normality
• Normality Testing in Excel: Chi-Squared Goodness-of-Fit Test
• Calculate descriptive statistics for the data
• Set up the hypothesis
• Understand the Chi-Squared Goodness-of-Fit test premise
• The Observed Bins & The Expected Bins

➡️ Chapter 19: Correlation and Regression

• Correlation and Regression
• Why work with correlation and regression at all?
• Correlation
• The Correlation Coefficient
• Calculating Correlation Coefficient in Excel
• CORREL Formula
• Data Analysis ToolPak
• Regression Analysis
• Different types of regressions
• 4 Types of Errors in Data
• Linear Regression Analysis
• Analyzing Regression Using the Data Analysis ToolPak
• Creating the Regression Worksheet
• Regression test with low correlation
• Using Correlation and Regression in Six Sigma
• Continuous and ratio data

➡️ UNIT 5: INTERMEDIATE STATISTICS

➡️ Chapter 20: Non-Normal Probability Distributions

• Non-Normal Probability Distributions
• Reviewing Normal Probability Distributions
• Anatomy of a Normal Curve
• The normal curve
• Non-Normal Continuous Distributions
• Exponential Distribution
• Lognormal Distribution
• Weibull Distribution
• Other Types of Continuous Distributions
• Cauchy Distribution
• Logistic Distribution
• Laplace Distribution
• Uniform Distribution
• Beta Distribution
• Gamma Distributions
• Triangular Distribution
• Non-Normal Discrete Distributions
• Binomial Distribution
• Poisson Distribution
• Other Types of Discrete Distributions
• Geometric Distribution
• Negative Binomial
• Applying Data to Real-World Situations

➡️ Chapter 21: Hypothesis Testing

• Hypothesis Testing
• The Basic Concept for Hypothesis Testing
• Hypothesis Test Basics
• How Hypothesis Testing Works?
• Null Hypothesis and Alternate Hypothesis
• Hypothesis Testing Calculation With Examples
• Null Versus Alternative
• Steps of Hypothesis Testing
• Hypothesis Testing and Confidence Intervals
• Simple and Composite Hypothesis Testing
• One-Tailed and Two-Tailed Hypothesis Testing
• Right Tailed Hypothesis Testing
• Left Tailed Hypothesis Testing
• The Risk of Hypothesis Testing Error
• Type 1 and Type 2 Error & Example
• Level of Significance
• P-Value
• Why is Hypothesis Testing Important in Research Methodology?
• Hypothesis Testing for Continuous Data - Normal & Non-Normal
• Hypothesis Testing Roadmap – Attribute Data
• Different Types of Hypothesis Testing
• Z test & T test
• Widely used T-tests
• One Sample T-Test
• Two Sample T-Test
• Paired T-Test
• Equal Variance T-Test
• Unequal Variance T-Test
• F test
• Chi-Square test
• ANOVA Test
• Selecting the Right Hypothesis Test
• Hypothesis Tests for Discrete Data
• 1-Proportion Test
• Example of the 1-Proportion Test
• 2 Proportion Test
• Example of the 2-Proportion Test
• Hypothesis Tests for Continuous Normal Data
• 1-Sample T Test (or Paired T Test)
• Example of the 1-Sample T Test
• Chi Square Test (or 1-Variance Test)
• Example of the Chi-Square Test (or 1-Variance Test)
• 2-Sample T Test
• Example of the 2-Sample T Test
• Hypothesis Tests for Continuous Non-Normal Data
• Chi-Square Test
• One Sample Wilcox
• Example of the One-Sample Wilcox
• Mann-Whitney Test
• Example of the Mann-Whitney Test
• Why Run Hypothesis Tests
• Running Hypothesis Tests
• Hypothesis Test Examples
• 1-Proportion Test
• Test and CI for One Proportion
• 1-Sample T Test
• 2-Sample T Test
• Two-Sample T-Test and CI: A, B
• One Sample Wilcox
• Wilcoxon Signed Rank Test: Bedrooms
• Hypothesis Testing in Analyze, Improve, and Control
• A Review of Hypothesis Testing Terms
• Limitations of Hypothesis Testing
• Common Pitfalls to Avoid During Hypothesis Testing

➡️ Chapter 22: Sample Size

• Sample Size
• Download Minitab
• A Review of Hypothesis Testing Errors
• Type I Error
• Type II Error
• What Information is Required for Choosing Sample Size?
• Questions to Ask About Alpha, Beta, and Delta Values
• Guidelines for Setting Various Numbers When Calculating Sample Size
• When Testing Means for Continuous Data
• When Testing Variance for Continuous Data
• When Testing Proportions for Discrete/Binomial Data
• Sample Size Calculations: Choosing the Right Method
• Running and Analyzing Sample Size Tests in Minitab
• Power and Sample Size
• 1-Sample Z Test
• Sample Calculations for a 1-Sample T Test
• 1-Sample t Test
• Backing into target power
• Sample Calculations for a 1-Sample Proportion Test
• Sample Size Calculations for a 2-Sample T Test
• 2-Sample t Test
• A Reminder Regarding Random Samples

➡️ Chapter 23: Advanced Control Charts

• Advanced Control Charts
• Common Control Chart Types and When to Use Them
• Creating and Reading Control Charts in Minitab
• Practice Interpreting Control Charts
• Running a Hypothesis Test
• Common Cause versus Special Cause Variation
• Additional Minitab Control Charts
• The I & MR Chart (Within/Between)
• Exponentially Weighted Moving Average
• Cumulative Sum

➡️ Chapter 24: Applying Statistics to Business Applications by Six Sigma

• Applying Statistics to Business Applications through Six Sigma
• Common Challenges When Presenting Statistical Analysis
• Why Include Some Statistics?
• Tips for Creating Business-Friendly Presentations
• Understand the Target Audience
• Tell a Story with Text and Images
• Be Clear and Concise
• Don’t Misuse Your Tools
• Don’t Let the Presentation Drive the Project

➡️ LEAN SIX SIGMA APPLICATIONS & CASE STUDY

• Six Sigma in Healthcare
• Benefits of Six Sigma in a Healthcare Environment
• Challenges of Implementing Six Sigma in a Healthcare Environment
• Six Sigma Healthcare Case Study: Virtua Health’s Cardiac Program
• Six Sigma Healthcare Case Study: Medical Transcription
• Tips For Using Six Sigma in Healthcare
• Six Sigma in Information Technology
• Benefits of Six Sigma in a Information Technology
• Challenges of Implementing Six Sigma in a IT Environment
• Six Sigma IT Case Study: Cellphone Provider Web Service
• Six Sigma IT Case Study: IT Components of Control
• Tips For Using Six Sigma in IT
• Six Sigma in Engineering
• Benefits of Six Sigma in an Engineering Environment
• Challenges of Implementing Six Sigma in an Engineering Environment
• Six Sigma Engineering Case Study: IE in the Automotive Industry
• Six Sigma Engineering Case Study: Consistent CAD and PLM Solutions
• Tips For Using Six Sigma in Engineering
• Six Sigma in Manufacturing
• Benefits of Using Six Sigma in Manufacturing Industry
• Challenges of Using Six Sigma in the Manufacturing Industry
• Six Sigma Case Study: Machines vs Human Capital
• Case Study: Increasing Machinery Throughput Without More Machines
• Tips For Using Six Sigma in Manufacturing Industry

➡️ LEAN SIX SIGMA EXCEL TEMPLATES

• 5S Audit Excel Checklist
• 5W2H Excel Template
• 8D Problem Solving Excel Template
• Automatic Histogram Excel Template
• Automatic Pareto Excel Template
• Automatic Scatter Chart
• Cause and Effect Diagram Excel Template
• Check Sheet Excel Template
• Control Plan Excel Template
• COQ and COPQ Calculation Excel Template
• Fishbone Diagram Template with Example
• GRR Study MSA Excel Template
• Kaizen Continuous Improvement Template
• Kaizen Excel Template
• Lean Six Sigma Project Charter Template
• MSA Gauge R&R Attribute Template
• OEE Excel Template
• PDCA Excel Template
• Process Flow Diagram Template
• Process FMEA Excel Template
• SPC Cp Cpk Study Excel Template
• SWOT Analysis Excel Template
• Why Why Analysis Excel Template
• SMART Goal Setting Excel Template

➡️ Tips for Successful Six Sigma Project

➡️ Limitations of Six Sigma Project

➡️ Advantages of Six Sigma Project

➡️ Disadvantages of Six Sigma Project

➡️ Benefits of Six Sigma Project