Foundations in Statistical Decision Making

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Ray Harkins, The Manufacturing Academy,Michael J. Vella

3:14:19

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1 - Introduction to the Course.mp4

06:33

2 - Comments on Software.mp4

06:18

3 - Course Topics.mp4

01:46

4 - Overview of Course Topics.mp4

00:52

5 - Why Statistical Experiments.mp4

01:13

6 - Alternatives to DOE.mp4

04:38

7 - Why Hypothesis Testing.mp4

01:48

8 - The Statistical View of Data.mp4

06:19

9 - Sampling and the Hypothesis Test.mp4

05:17

10 - Errors in Hypothesis Testing.mp4

04:25

11 - Tools and Requirements of Statistical Design.mp4

01:37

12 - Tools and Requirements of Statistical Design.mp4

03:09

13 - T test Examples in Hypothesis Testing.mp4

06:58

14 - T tests in Excel.mp4

14:18

14 - T-Test.xlsx

15 - Z tests in Hypothesis Testing Pt 1.mp4

06:44

16 - Z tests in Hypothesis Testing Pt 2.mp4

06:41

17 - More Z test Examples.mp4

10:26

18 - Z test in Excel.mp4

04:03

18 - Z-Test.xlsx

19 - Z tests of Proportions.mp4

07:29

20 - Conclusion to Hypothesis Testing.mp4

01:11

21 - Introduction to a DOE Pt 1.mp4

03:14

22 - Introduction to a DOE Pt 2.mp4

03:44

23 - DOE Terminology.mp4

07:58

24 - Tips for a Successful DOE.mp4

02:39

25 - Types of Experimental Designs.mp4

02:06

26 - Additional DOE concepts.mp4

08:48

27 - ANOVA and the F Distribution.mp4

06:27

28 - ANOVA in Excel.mp4

03:49

29 - Twoway ANOVA Overview.mp4

01:59

30 - F-Distribution.xlsx

30 - Twoway ANOVA in Excel.mp4

05:58

31 - Full Factorial Experiments Pt 1.mp4

02:57

32 - Full Factorial Experiments Pt 2.mp4

09:21

33 - Fractional Factorial Designs and Taguchi Methods.mp4

08:01

34 - Taguchi Case Study Pt 1.mp4

05:23

35 - Taguchi Case Study Pt 2.mp4

09:05

36 - Taguchi Case Study Pt 3.mp4

01:40

37 - Concluding Notes and References.mp4

02:43

38 - Conclusion to the Course.mp4

02:55

39 - Additional-Course-Links-012223.docx

39 - Additional-Course-Links-012223.pdf

39 - Bonus Lecture.mp4

03:47

Description

Hypothesis Testing, ANOVA, and Design and Analysis of Experiments (DOE) for the Manufacturing Professional

What You'll Learn?

How to conduct experiments and analyze the resulting data to help make better technical decisions about equipment, processes and measurement systems
An intermediate-level statistical tool kit aimed at the manufacturing professional
Practical examples and case studies from a manufacturing setting
Hypothesis Testing - What is it and How to apply it?
T tests, Z tests - With examples in Microsoft Excel
Design and Analysis of Experiments (DOE)
DOE terminology and techniques
ANOVA, One and Two Factor - Also with examples in Microsoft Excel
Full Factorial Experiments
Fractional Factorial Experiments
Taguchi Experimental Methods

Who is this for?

Industrial engineers, Manufacturing engineers

Quality engineers and quality technicians

Process engineers and process technicians

Manufacturing managers

More details

Description
Effective decision making is what separates successful manufacturing professionals from everyone else. And to make effective technical decision, you must correctly understand, analyze and interpret the data.
More than hazarding a guess or using simple tools like averages and visualizations, this class will teach you a broad selection of intermediate-level statistical tools useful in solving your difficult quality, engineering and process improvement problems.
Topics in Foundations in Statistical Decision Making include:
The benefits and advantages of statistical experiments
Hypothesis testing - where and why it's used.
Error in hypothesis testing
Designing a statistical experiment
T tests for means
Z tests for means and proportions
Design and analysis of experiments (DOE)
Practical tips for a successful DOE
One and two factor analysis of variance (ANOVA)
Full factorial experiments
Fractional factorial experiments
An introduction to Taguchi Methods
A case study showing an L8 Taguchi experiment
Lots of real-life examples from manufacturing
References for your further study
And MUCH more
Unlike some classes taught from a purely academic perspective with little connection to the real world, this class was designed and taught by manufacturing professionals for manufacturing professionals. By the time you are done with this course, you will have a clear understanding how to use statistical models in your work, and be prepared to continue your training onto to more advanced statistical tools.
So if you're a manufacturing, quality, process or industrial engineer or manager looking to take the next step in your decision making skills, this is the class for you!!
Sign up today!!
Who this course is for:
Industrial engineers, Manufacturing engineers
Quality engineers and quality technicians
Process engineers and process technicians
Manufacturing managers

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Ray Harkins is a senior manufacturing professional with 30 years experience in manufacturing engineering, quality management, and business analysis. During his career, he has toured hundreds of manufacturing facilities and worked with leading industry professionals throughout North America and Japan. He earned his Bachelor of Science from the University of Akron where he majored in Engineering Technology, his Master of Science from Rochester Institute of Technology where he majored in Manufacturing Leadership and Project Management, and his Master of Business Administration from Youngstown State University. He is a senior member of the American Society of Quality, and holds their Quality Engineering (CQE), Quality Technician (CQT), Quality Auditing (CQA) and Calibration Technician (CCT) certifications. Ray has written extensively for national trade publications on the topics of quality engineering and career management, and has taught over 32,000 students through the Udemy platform on a range of manufacturing-related topics.

Michael J. Vella

Instructor's Courses

Mike Vella has joined the Udemy Instructors team on the Manufacturing Academy site following a 42-year career in Quality and Operations in the Automotive and Food Manufacturing industries. Most recently, Mike retired in 2021 as Senior VP Operations at the Suter Company an employee-owned food producer located in Sycamore, Illinois. Prior to joining Suter, Mike was the Vice President and General Manager of TI Automotive’s Brake and Fuel Group in North America before retiring in 2006. Mike was with TI Automotive for 30 years. Mike received his MBA from Wayne State University and his BS from Western Michigan University.Mike believes that a leader’s legacy is partially formed by sharing what you know they know and what they have experienced to develop others along their own path in life. Mike was a frequent speaker and trainer at TI Automotive and with The Suter Company along with his support of education within the American Society for Quality, Greater Detroit section and the Automotive Division. A Senior Member and Fellow of the ASQ, Mike retains his certification as a Quality Engineer and Reliability Engineer. Mike has been honored as Greater Detroit Section Man of the Year. Mike resides in Aurora, Illinois with his wife Lynne.

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