Six Sigma Tools – V : Statistical tools – Hypothesis testing, Chi square test, t-test, ANOVA

Description

INTRODUCTION

This course on Six Sigma Tools – V : Statistical tools – Hypothesis testing, Chi square test, t-test, ANOVA is part of the Six Sigma Specialization series that is designed to give an introductory and intermediate level of familiarization of Six Sigma concepts and tools.

Six Sigma is a systematic improvement process leading to process design / redesign. It uses several statistical tools and is widely applicable to any process – be it in manufacturing or functional areas. The benefits of Six Sigma are widely acknowledged in several industries and for several different processes – many industries have saved many millions of dollars

Six Sigma coupled with other processes like lean manufacturing form a lethal combination leading to radical improvements and huge savings of time, effort and money.

An understanding of the principles is essential for all – both in management and technical workforce.

LEARNING OBJECTIVES

This course covers the Six Sigma Tools – V : Statistical tools – Hypothesis testing, Chi square test, t-test, ANOVA. 

Hypothesis testing tells us whether there exists statistically significant difference between the data sets for us to consider that they represent different distributions.

Steps in Hypothesis Testing which will be described :

1. Determine appropriate Hypothesis test
2. State the Null Hypothesis Ho and Alternate Hypothesis H_a
3. Calculate Test Statistics / P-value against table value of test statistic
4. Interpret results – Accept or reject H_o

Continuous and discrete are two different categories of data often used to measure processes. Continuous data can assume a range of numerical responses on a scale that is continuous – weight, width, length, height and temperature can all be measured in order to provide types of continuous data. Discrete data is measured by the presence or absence of a particular characteristic in each device that is being tested – it can be used to measure defects or something that is altogether intangible.

Types of Six Sigma Hypothesis Testing are based on the type of data.

1. Normal Continuous Y and Discrete X
2. Non-Normal Continuous Y and Discrete X
3. Continuous Y and Continuous X
4. Discrete Y and Discrete X

We will discuss these topics in this course.  

On completion of this series, the user will have a good knowledge of:

• Tools used in Define stage – Project charter, Thought map, SIPOC, Value Stream Map, Zero Loss studies to identify bottleneck machine / operation (in manufacturing), Cause and Effect matrix, Failure Mode Effect Analysis
• Measuring the process – Measurement System Analysis. This may be more relevant for processes related to manufacturing
• Improvement methods and related statistical tools of Hypothesis testing – Chi squared test, t test, Analysis of variance (ANOVA)
• Control strategies for sustenance of the improvements made by design or redesign of processes

After this series, the participant can appreciate any topic on Six Sigma which are at fundamental or intermediate levels. On completion of the series the participant will be ready to enroll in Advanced courses on Six Sigma that lead to a formal certification as a White Belt or Yellow Belt or Green Belt or Black Belt.

ALL of our courses in this series is developed based on decades of front-line industry experience of the instructor. 

WHO SHOULD TAKE THIS COURSE

Anyone who is involved with any process, be it manufacturing or transactional. It is uniformly applicable across any function. This course is equally important to any operator or management staff.

The series should form mandatory knowledge for any professional in manufacturing or Supply Chain or Project Management or HR or any function and especially a new employee.

This course is ALSO part of the is a Bundled Specialization course titled Six Sigma Specialization. You might also want to consider  to take the course on Lean Manufacturing Tools Specialization along with this course.

COURSE CONTENT 

• INTRODUCTION
• BASICS
• HYPOTHESIS TESTING
  • Overview – Statistical testing
  • Statistical significance & Confidence Interval
  • Basic terminology & decision errors
  • Procedure – Hypothesis Testing
  • Examples of hypothesis testing
  • Tools for Evaluating X vs Y
• CHI-SQUARE TEST
  • When to use
  • How to use – Example
  • Steps through an example
  • Chi-square analysis with MINITAB
• t-TEST
  • Types of t-tests
  • Example : 1-sample t-test
  • Example : 2-sample t-test
  • Example : paired t-test
• ANOVA
  • F-Distribution
  • F-Distribution : Concept Animation
  • ANOVA example
  • ANOVA example – Steps
  • ANOVA example – MINITAB
  • ANOVA options
• REFERENCES & COURSE HANDOUTS
• FINAL QUIZ