Lean Six Sigma and Business Process

Introduction to Business Statistics

• Traditional Classroom: 3-day
• Virtual Instructor-led: Six 3-hour sessions

This three-day instructor-led course is intended to provide participants with hands-on application of statistical concepts and methods that are useful in daily business activity. Utilizing a real world case study with both manufacturing and transactional examples, participants will work in teams to determine what should be measured and how data should be accurately collected, recorded, and analyzed to make well-informed decisions and improve results.

Target Audience

The primary audience for this course is process owners or managers with minimal to no experience in working with statistical data and reports.

Learning Objectives

• Determine when and why to collect key performance data.
• Accurately stratify, sample, and collect data.
• Write operational definitions to ensure accurate data collection.
• Identify variation types and causes.
• Determine data distributions and signals.
• Describe variability through confidence intervals.
• Analyze data numerically and graphically to gain useful information.

Key Takeaways

• Enhanced understanding of the power of data
• Competent in establishing measurements of key performance outputs and inputs
• Ability to use and interpret basic statistics in numerical and graph forms
• Familiarity of advanced statistical methods

Course Outline

Module 0: Welcome and Introductions

• Team Facilitation Tips and Techniques

Module 1: Measure

• Define the Power of Using Statistics in Business
• Determine Benefits of Measurement
• Qualify Outputs (Y) And Inputs (X)
• Distinguish Difference Between Continuous and Discrete Data
• Exercise: Identify Data Types

Module 2: What Data to Collect

• Determine Different Sources of Data
• Understand Limitations of Analysis Based on Data Source
• Stratify Data
• Determine Sampling Strategy
• Write Operational Definition
• Exercises: Case Study Intro and Write Operational Definition

Module 3: Accurate Data Collection

• Develop a Complete and Accurate Measurement System
• Create a Data Collection Plan
• Format Data Collection Sheets
• Exercise: Data Collection Planning

Module 4: The Concept of Variation

• Determine Why Variation Should Be Tracked
• Describe The Difference Between Common Cause Factors And Special Cause Factors
• Plot Basic Data In A Control Chart To Monitor Variation
• Exercises: Process Variation Demonstration, Control Chart Analysis

Module 5: Descriptive Statistics

• Describe the Importance of Descriptive Statistics in Various Types of Data
• Distinguish Which Measures Are Best Used in Certain Circumstances
• Determine What Can Be Learned from Shape of Data
• Exercises: Descriptive Statistics Analysis, Distribution Analysis

Module 6: Confidence Intervals

• Define the Difference Between Samples and Population.
• Develop Confidence Intervals for Levels and Proportions.

Module 7: Graphical Representations

• Identify Appropriate Graphical Tool for a Given Dataset
• Analyze Various Plots and Charts
• — Times Series Plot
• — Histogram
• — Dot Plot
• — Box Plot
• — Pareto Chart
• — Scatter Plot
• Exercises: Review Case Study Charts for Analysis

Module 8: Probability Concepts

• Calculate Probability of an Event
• Calculate Probability of a Union

Module 9: Normal Distributions

• Define a Standard Normal Distribution
• Describe the Central Limit Theorem

Module 10: Advanced Statistics

• Set up the Factors For a 2-Sample t-Test
• Recognize the Need for Hypothesis Testing
• Analyze the Results of a Correlation Test
• Analyze the Statistics of a Basic Regression Analysis
• Exercise: Set up Tests for Case Study

Module 11: Course Summary and Action Plan

• Summary
• Action Planning
• Exercise: Teach Back with Review Questions

MDI877 Course Code