Data Analytics for Lean Six Sigma

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Beschreibung

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About this course: Welcome to this course on Data Analytics for Lean Six Sigma. In this course you will learn data analytics techniques that are typically useful within Lean Six Sigma improvement projects. At the end of this course you are able to analyse and interpret data gathered within such a project. You will be able to use Minitab to analyse the data. I will also briefly explain what Lean Six Sigma is. I will emphasize on use of data analytics tools and the interpretation of the outcome. I will use many different examples from actual Lean Six Sigma projects to illustrate all tools. I will not discuss any mathematical background. The setting we chose for our data example is a Lean …

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Frequently asked questions

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Noch nicht den perfekten Kurs gefunden? Verwandte Themen: Data Analytics, Lean Six Sigma, Six Sigma, Lean und Lean.

When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: Welcome to this course on Data Analytics for Lean Six Sigma. In this course you will learn data analytics techniques that are typically useful within Lean Six Sigma improvement projects. At the end of this course you are able to analyse and interpret data gathered within such a project. You will be able to use Minitab to analyse the data. I will also briefly explain what Lean Six Sigma is. I will emphasize on use of data analytics tools and the interpretation of the outcome. I will use many different examples from actual Lean Six Sigma projects to illustrate all tools. I will not discuss any mathematical background. The setting we chose for our data example is a Lean Six Sigma improvement project. However data analytics tools are very widely applicable. So you will find that you will learn techniques that you can use in a broader setting apart from improvement projects. I hope that you enjoy this course and good luck! Dr. Inez Zwetsloot & the IBIS UvA team

Who is this class for: This course is aimed at anyone who would like to learn more about data analytics tools and Lean Six Sigma. No prior knowledge (data analytics or Lean Six Sigma) is required.

Created by:  University of Amsterdam
  • Taught by:  Inez Zwetsloot, Dr.

    Amsterdam Business School, Economics & Business
Level Beginner Commitment 5 weeks of study, 2-4 hours per week. Language English How To Pass Pass all graded assignments to complete the course. User Ratings 4.8 stars Average User Rating 4.8See what learners said Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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University of Amsterdam A modern university with a rich history, the University of Amsterdam (UvA) traces its roots back to 1632, when the Golden Age school Athenaeum Illustre was established to train students in trade and philosophy. Today, with more than 30,000 students, 5,000 staff and 285 study programmes (Bachelor's and Master's), many of which are taught in English, and a budget of more than 600 million euros, it is one of the largest comprehensive universities in Europe. It is a member of the League of European Research Universities and also maintains intensive contact with other leading research universities around the world.

Syllabus


WEEK 1


Data and Lean Six Sigma



This module introduces Lean Six Sigma and shows you where data and data analytics have their place within the DMAIC framework. It also introduces the software package Minitab. This package is used throughout the videos for data analytics. It is not mandatory to use this package. I just really like it!


11 videos, 4 readings, 1 practice quiz expand


  1. Video: Introduction to Data Analytics for Lean Six Sigma
  2. Video: Let me introduce myself!
  3. Reading: Let me introduce IBIS UvA
  4. Video: M1-V1 Introduction to Lean Six Sigma
  5. Video: M1-V2 Data and DMAIC
  6. Video: M1-V3 Selecting CTQs
  7. Video: M1-V4 Units and operational definition
  8. Video: M1-V5 Sampling
  9. Video: M1-V6 Organizing your data
  10. Reading: Overview videos
  11. Reading: Minitab: what is it?
  12. Video: M1-V7 Installing Minitab
  13. Video: M1-V8 Introduction to Minitab
  14. Video: M1-V9 Loading data into Minitab
  15. Reading: Explanation quizzes
  16. Practice Quiz: Practice quiz - Data and Lean Six Sigma

Graded: Graded quiz - Data and Lean Six Sigma

WEEK 2


Understanding and visualizing data



This module explains how to visualize data. It discusses visualizing single variables as well as visualizing two variables. You will learn to select the appropriate graph. For this it is essential to first learn the distinction between numerical and categorical data.


8 videos, 3 readings, 1 practice quiz expand


  1. Video: M2-V1 Numerical and categorical data
  2. Reading: Data needed for the next videos!
  3. Video: M2-V2 Descriptive statistics
  4. Video: M2-V3 Visualizing numerical data
  5. Video: M2-V4 Visualizing categorical data
  6. Video: M2-V5 Pareto analysis
  7. Video: M2-V6 Visualizing two variables
  8. Reading: Video exercises
  9. Video: M2-V7 Exercise - Investigation time
  10. Video: M2-V8 Exercise - Coffee batch
  11. Reading: Explanation quizzes
  12. Practice Quiz: Practice quiz - Understanding and visualizing data

Graded: Graded quiz - Understanding and visualizing data

WEEK 3


Using probability distributions
In this module on using probability distributions, you will learn how to quantify uncertainty. Furthermore you will learn to answer an important business question: “what percentage of products or cases meet our specifications?".


7 videos, 1 reading, 1 practice quiz expand


  1. Video: M3-V1 Population versus sampling
  2. Video: M3-V2 Estimation and confidence intervals
  3. Video: M3-V3 Normal, Lognormal and Weibull distribution
  4. Video: M3-V4 Probability plot
  5. Video: M3-V5 Empirical CDF
  6. Video: M3-V6 Properties of the normal distribution
  7. Video: M3-V7 Exercise - Length of Stay
  8. Reading: Explanation quizzes
  9. Practice Quiz: Practice quiz - Using probability distributions

Graded: Graded quiz - Using probability distributions

WEEK 4


Introduction to testing
You will learn to model your CTQ and influence factor(s) and to use a decision tree to select the appropriate tool for data based testing of this model. Furthermore, causality is introduced.


3 videos, 1 reading, 1 practice quiz expand


  1. Video: M4-V1 Introduction to data analysis
  2. Video: M4-V2 Hypothesis testing
  3. Video: M4-V3 Causality
  4. Reading: Explanation quizzes
  5. Practice Quiz: Practice quiz - Introduction to testing


Testing: numerical Y and categorical X
In this module on statistical testing, you will learn how to establish relationship between a numerical Y variable (the CTQ) and categorical influence factors (the X variables).


8 videos, 2 readings, 1 practice quiz expand


  1. Video: M5-V1 Introduction to ANOVA
  2. Video: M5-V2 ANOVA analysis
  3. Video: M5-V3 ANOVA residual analysis
  4. Video: M5-V4 Kruskal-Wallis test
  5. Video: M5-V5 Two sample t-test
  6. Reading: Note on video M5-V6
  7. Video: M5-V6 Test for equality of variances
  8. Video: M5-V7 Exercise - Productivity
  9. Video: M5-V8 Exercise - Department
  10. Reading: Explanation quizzes
  11. Practice Quiz: Practice quiz - Testing: numerical Y and categorical X

Graded: Graded quiz - Introduction to testing & Testing: numerical Y and categorical X

WEEK 5


Testing: numerical Y and numerical Y
What is the relation between the length of stay and the age of a patient? In this module you will learn to answers these types of questions using statistical tests to relate a numerical CTQ (the Y variable) to a numerical influence factor (the X variable).


7 videos, 1 reading, 1 practice quiz expand


  1. Video: M6-V1 Correlation
  2. Video: M6-V2 Introduction to regression
  3. Video: M6-V3 Regression analysis
  4. Video: M6-V4 Regression residual analysis
  5. Video: M6-V5 Regression prediction interval
  6. Video: M6-V6 Quadratic regression
  7. Video: M6-V7 Exercise - picking
  8. Reading: Explanation quizzes
  9. Practice Quiz: Practice quiz - Testing: numerical Y and numerical X


Testing: categorical Y
Finally you will learn how to test a relationship between a Y and a X variable whenever your Y variable (the CTQ) is a categorical variable.


4 videos, 1 reading, 1 practice quiz expand


  1. Video: M7-V1 Chi-square analysis
  2. Video: M7-V2 Logistic regression
  3. Video: M7-V3 Exercise - printers
  4. Video: M7-V4 Exercise - students
  5. Reading: Explanation quizzes
  6. Practice Quiz: Practice quiz - Testing: categorical Y

Graded: Graded quiz - Testing: numerical Y and numerical X & Testing: categorical Y

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