Principles of Graphing Data

A picture may be worth a thousand words, but some pictures get the message across better than others. In this session, we’ll discuss the principles of how to create good graphs and what makes one graph type better than another for conveying information.

We’ll start by covering graphs for one variable and progress through graphs that show relationships among many variables, presenting different types of graphs for different types of data.

We’ll cover when to use various types of graphing elements like bars, lines, or points. And we’ll even answer the question: is there ever a good time to use a pie chart?

These principles are applicable in not only science and engineering, but any field where you want a visual summary of the data you have collected.

Di has been a JMP user since 1998, and now has the job of her dreams, teaching people to extract information from their data using JMP. She received a PhD in statistics in 1994 and an MS in mathematics in 1988 from Texas A&M University. Di has many years of experience as a statistician in the semiconductor industry. Her research interests include statistical process control and design of experiments, especially when data are auto-correlated, factors are random or other non-textbook situations occur.

One of Di’s students said: “Di is the best instructor I have ever experienced in my career. Her knowledge and experience make the course very valuable.”

Scott Lee Wise is a Senior Systems Engineer for JMP Statistical Discovery, a subsidiary of SAS Institute. In this role Scott helps customers solve their process/design pain points and tell the story in their data through the use of JMP analytic software products. 

Previously, Scott held roles in global technical enablement, education management and instruction, and data science at the company. Previous work experience also covers quality, engineering, and business intelligence roles within the manufacturing, technology, and textile industries.  

Scott attained degrees in both Business (BSBA from UNC Chapel Hill) and Quality Engineering practices (MSQA from SPSU). Scott also holds ASA Professional Statistician, ASQ Quality Engineering/Management, JMP and SAS Software, Master Black Belt and PMI Project Management certifications. 

He is currently based in the San Francisco Bay Area.