# Data Analytics with Lean six sigma

3 Months

• Understanding and visualizing data
• Visualizing data using Tableau
• Visualizing data using Python
• Visualizing data using R
• Basic Statistics using Excel
• Data and Lean Six Sigma
• Using probability distributions
• Introduction to testing
• Testing: numerical Y and categorical X
• Testing: numerical Y and numerical Y
• Testing: categorical Y
• Assignments for assessment
• One Project

Course Outline

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.

Visualizing data using Tableau

This module explains how to visualize data using Tableau. It discusses the hands on for connecting to data, charts and graphs, Creating Dashboard and Story.

Visualizing data using Python

This module explains how to visualize data using Python. It discusses the hands on for creating graphs and calculating descriptive statistics.

Visualizing data using R

This module explains how to visualize data using R. It discusses the hands on for creating graphs and calculating descriptive statistics.

Basic Statistics using Excel

This module explains how to visualize data using Excel. It discusses the hands on for creating graphs and calculating descriptive statistics.

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!

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?”.

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.

Testing: numerical Y and categorical X

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

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 answer these types of questions using statistical tests to relate a numerical CTQ (the Y variable) to a numerical influence factor (the X variable).

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.

• Assignments for assessment
• One Project