Definition and characteristics of IT project managementCopyCopy

Common reasons why IT projects failCopyCopy

Types of riskCopy

Components of risk management Identification Quantification Response development Response controlCopy

1.1 The Basics of Six Sigma

1.1.1 Meanings of Six Sigma

1.1.2 General History of Six Sigma & Continuous Improvement

1.1.3 Deliverables of a Lean Six Sigma Project

1.1.4 The Problem Solving Strategy Y = f(x)

1.1.5 Voice of the Customer, Business and Employee

1.1.6 Six Sigma Roles & Responsibilities

1.2.1 Defining a Process

1.2 The Fundamentals of Six Sigma

1.2.2 Critical to Quality Characteristics (CTQ’s)

1.2.3 Cost of Poor Quality (COPQ)

1.2.4 Pareto Analysis (80:20 rule)

1.2.5 Basic Six Sigma Metrics

1.3 Selecting Lean Six Sigma Projects

1.3.2 Developing Project Metrics

1.3.1 Building a Business Case & Project Charter

1.3.3 Financial Evaluation & Benefits Capture

1.4 The Lean Enterprise

1.4.1 Basics of Lean

1.4.3 Lean & Six Sigma Integration

1.4.2 History of Lean

1.4.5 5S – Straighten, Shine, Standardize, Self-Discipline, Sort

1.4.4 The Seven Elements of Waste

Risk management planningCopy

Risk identificationCopy

Idea generation tools and techniqueCopy

Process Mapping (As-Is Process)

Data Attributes (Continuous Versus Discrete)

Defining Metrics

Measurement System Analysis

Gage Repeatability And Reproducibility

Data Collection Techniques

Calculating Sample Size

Data Collection Plan

Understanding Variation

Measuring Process Capability

Calculating Process Sigma Level

Rolled Throughput Yield

Measurement Phase Review

Statistical Software Training

Visually Displaying Baseline Performance

Probability and impactCopy

Presenting risk Narrative Qualitative QuantitativeCopy

Probability analysisCopy

3.1 Patterns of Variation

3.1.1 Multi-Vari Analysis

3.1.2 Classes of Distributions

3.2 Inferential Statistics

3.2.1 Understanding Inference

3.2.2 Sampling Techniques & Uses

3.2.3 Central Limit Theorem

3.3 Hypothesis Testing

3.3.1 General Concepts & Goals of Hypothesis Testing

3.3.2 Significance; Practical vs. Statistical

3.3.3 Risk; Alpha & Beta

3.4 Hypothesis Testing with Normal Data

3.4.1 1-sample & 2 sample t-tests

3.4.2 One-Way ANOVA

3.4.3 Two-Way ANOVA

3.5 Hypothesis Testing with Non-Normal Data

3.5.1 Mann-Whitney

3.5.2 Kruskal-Wallis

3.5.3 Mood’s Median

3.5.4 Friedman

3.5.5 1 Sample Sign

3.5.6 1 Sample Wilcoxon

3.5.7 One and Two Sample Proportion

3.5.8 Chi-Squared (Contingency Tables)

Determining risk tolerancesCopy

Analysing risksCopy

Establishing and evaluating profitabilityCopy

Risk‐based financial tools and techniquesCopy

Expected‐value analysisCopy

Decision treesCopy

Prioritising risksCopy

4.1 Simple Linear Regression

4.1.1 Correlation

4.1.2 Regression Equations

4.1.3 Residuals Diagnostics Analysis

4.2 Multiple Regression Analysis

4.2.1 Non-Linear Regression

4.2.2 Multiple Linear Regression

4.2.3 Confidence & Prediction Intervals

4.2.4 Residuals Diagnostics Analysis

4.2.5 Data Transformation, Box Cox Technique

4.3 Designed Experiments

4.3.1 Experimental Objectives

4.3.2 Experimental Methods

4.3.3 Experiment Design Considerations

4.4 Full Factorial Experiments

4.4.1 2k Full Factorial Designs

4.4.2 Linear & Quadratic Mathematical Models

4.4.3 Balanced & Orthogonal Designs

4.4.4 Fit, Diagnose Model and Center Points

4.5 Fractional Factorial Experiments

4.5.1 Designs

4.5.2 Confounding Effects

4.5.3 Experimental Resolution

4.6 Advanced Experiments

4.6.1 Steepest Ascent Analysis

Describe the major activities of the preliminary and detailed design activitiesCopyCopy

Risk acceptanceCopy

Risk avoidanceCopy

Risk mitigation Probability minimisation Impact minimisation TransferenceCopy

Establishing reservesCopy

5.1 Lean Controls

5.3.1 Control Methods for 5S

5.3.2 Kanban (Pull Systems)

5.3.3 Poka-Yoke (Mistake Proofing)

5.2 Statistical Process Control (SPC)

5.4.1 Data Collection for SPC

5.4.2 I-MR Chart

5.4.3 Xbar-R Chart

5.4.4 U Chart

5.4.5 P Chart

5.4.6 NP Chart

5.4.7 Xbar-S Chart

5.4.8 CumSum Chart

5.4.9 EWMA Chart

5.4.10 Control Methods

5.3 Six Sigma Control Plans

5.6.1 Cost Benefit Analysis

EXAM DAY ON THE LAST DAY

5.6.2 Elements of the Control Plan

EXAM DAY ON THE LAST DAY

5.6.3 Elements of the Response Plan

Risk Response monitoring and controlCopy

Describe quality assurance activities, testing and auditsCopyCopy

Contingency plans and work‐aroundsCopy

Risk evaluationCopy

Reassessing riskCopy

Risk documentationCopy