Foundations of Data Analysis for Product and Process Improvement
Cy Wegman, Course Author
Senior Analyst and Statistical Consultant at Predictum Inc.
3 days
On-premises or virtual
Available on request
About This Course
It’s essential that you not only master core data analysis skills, but that you quickly apply them to your work.Â
That’s why Foundations of Data Analysis for Product and Process Improvement provides you with the hands-on skills you need to get ahead.Â
During the course, you will master basic to advanced analytical methods, you will solve problems that arise in real-world scenarios, and most importantly, you will improve the effectiveness of your work.Â
Fundamental data analysis skills. These include:
- Creating samples and calculating appropriate sample sizes
- Describing and analyzing distributions of data
- Performing graphical analysis, hypothesis testing, analysis of variance, and model building
- Solving scientific and engineering problems from single to multiple factors and responses
- Identifying and overcoming statistical challenges
The fundamental skills needed to understand and use JMP. These include:
- Importing and arranging data
- Avoiding time-consuming tasks using JMP productivity features
- Solving formatting challenges using JMP tools
- Visualizing and exploring your data
- Converting data into presentations
Skills to uncover deep insights into your products and processes.
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Day One
- Introduction to JMP
- Navigating JMPÂ
- Data Cleaning
- Data Exploration
- Graphical Analysis
- Univariate Graphs
- Bivariate Graphs
- Â Multivariate Graphs
Day Two
- Inferential Analysis
- Means Tests
- Standard Deviation/Variance Tests
- Proportion TestsÂ
- Testing for Normality
- Intervals
- Confidence Intervals
- Prediction Intervals
- Tolerance Intervals: Establishing Expectations and Specifications
Day Three
- ANOVA
- Analysis of Variance
- Â One-Way ANOVA in JMP
- Multiple Comparisons
- Nonparametric Tests
- Model BuildingÂ
- ANOVA
- Regression
- Combine Continuous and Nominal Factors
- Design of Experiments (DOE)
Instructors
Before joining Predictum, he worked for 38 years at Procter & Gamble, where his last assignment was the Empirical Modeling leader for the company. Cy is a member of the P&G Prism Society, which represents the top 1% of P&G engineers, for profitably applying his technical mastery. His contributions have resulted in hundreds of millions of dollars in annual savings. His cross-industry work in manufacturing, engineering, and R&D has spanned molecular-scale to full-scale technologies, as well as material, formulation, process, packaging, and consumer models.
Cy holds a B.S. in Civil Engineering from Rose-Hulman Institute of Technology.
Marie is Professor Emerita of Statistics at the University of New Hampshire (UNH), where she has worked extensively with students and companies on the practical application of statistics. She is also a co-author of two books, one of which is about the use of JMP software and statistical methods to improve quality and the other is about the partial least squares technique. She was also a statistical writer for several years as a member of the JMP documentation team at SAS Institute.
Marie holds a Ph.D. in Statistics from the University of Massachusetts at Amherst.
Who Should Attend
Engineers, scientists and technicians responsible for product and process development
Duration
3 days
Delivery Methods
On premises or virtual
Prerequisites
Familiarity with computers and spreadsheet software, such as Microsoft Excel.
JMP is required if you want to actively participate in the course. If you do not have JMP you can get a free trial version to install on your work or personal computer.
Pricing
Individual and group pricing available on request
Register Now
Foundations of Data Analysis for Product and Process Improvement
Please complete the information below. Our team will be in touch with you to schedule your course.Â
Additional questions? Contact amingo@predictum.com.
We look forward to working with you soon!
