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Lecture 23: Probability theory
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Classroom Contents
Six Sigma
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- 1 Six Sigma-Introductory Video
- 2 Lecture 1: Brief overview of the course
- 3 Lecture 2: Quality concepts and definition
- 4 Lecture 03: History of continuous improvement
- 5 Lecture 4: Six Sigma Principles and Focus Areas (Part 1)
- 6 Lecture 5: Six Sigma Principles and Focus Areas (Part 2)
- 7 Lecture 6: Six Sigma Applications
- 8 Lecture 07 : Quality Management: Basics and Key Concepts
- 9 Lecture 8: Fundamentals of Total Quality Management
- 10 Lecture 9: Cost of quality
- 11 Lecture 10: Voice of customer
- 12 Lecture 11: Quality Function Deployment (QFD)
- 13 Lecture 12: Management and Planning Tools (Part 1)
- 14 Lecture 13: Management and Planning Tools (Part 2)
- 15 Lecture 14: Six Sigma Project Identification, Selection and Definition
- 16 Lecture 15: Project Charter and Monitoring
- 17 Lecture 16: Process characteristics and analysis
- 18 Lecture 17: Process Mapping: SIPOC
- 19 Lecture 18: Data Collection and Summarization (Part 1)
- 20 Lecture 19: Data Collection and Summarization (Part 2)
- 21 Lecture 20: Measurement systems: Fundamentals
- 22 Lecture 21: Measurement systems analysis: Gage R&R study
- 23 Lecture 22: Fundamentals of statistics
- 24 Lecture 23: Probability theory
- 25 Lecture 24: Process capability analysis: Key Concepts
- 26 Lecture 25: Process capability analysis: Measures and Indices
- 27 Lecture 26: Process capability analysis: Minitab Application
- 28 Lecture 27: Non-normal process capability analysis
- 29 Lecture 28: Hypothesis testing: Fundamentals
- 30 Lecture 29: Hypothesis Testing: Single Population Test
- 31 Lecture 30: Hypothesis Testing: Two Population Test
- 32 Lecture 31: Hypothesis Testing: Two Population: Minitab Application
- 33 Lecture 32: Correlation and Regression Analysis
- 34 Lecture 33: Regression Analysis: Model Validation
- 35 Lecture 34: One-Way ANOVA
- 36 Lecture 35: Two-Way ANOVA
- 37 Lecture 36: Multi-vari Analysis
- 38 Lecture 37: Failure Mode Effect Analysis (FMEA)
- 39 Lecture 38: Introduction to Design of Experiment
- 40 Lecture 39: Randomized Block Design
- 41 Lecture 40: Randomized Block Design: Minitab Application
- 42 Lecture 41: Factorial Design
- 43 Lecture 42: Factorial Design: Minitab Application
- 44 Lecture 43: Fractional Factorial Design
- 45 Lecture 44: Fractional Factorial Design: Minitab Application
- 46 Lecture 45: Taguchi Method: Key Concepts
- 47 Lecture 46: Taguchi Method: Illustrative Application
- 48 Lecture 47: Seven QC Tools
- 49 Lecture 48: Statistical Process Control: Key Concepts
- 50 Lecture 49: Statistical Process Control: Control Charts for Variables
- 51 Lecture 50: Operating Characteristic ,(OC)
- 52 Lecture 51: Statistical Process Control: Control Charts for Attributes
- 53 Lecture 52: OC, Curve for Attribute control chart
- 54 Lecture 53: Statistical Process Control: Minitab Application
- 55 Lecture 54: Acceptance Sampling: Key Concepts
- 56 Lecture 55: Design of Acceptance Sampling Plans for Attributes (Part 1)
- 57 Lecture 56: Design of Acceptance Sampling Plans for Attributes (Part 2)
- 58 Lecture 57: Design of Acceptance Sampling Plans for Variables
- 59 Lecture 58: Acceptance Sampling: Minitab Application
- 60 Lecture 59: Design for Six Sigma (DFSS): DMADV, DMADOV
- 61 Lecture 60: Design for Six Sigma (DFSS): DFX
- 62 Lecture 61: Team Management
- 63 Lecture 62: Six Sigma: Case study
- 64 Lecture 63: Six Sigma: Summary of key concepts
