Seminars: Visualize and communicate your data analysis more effectively

Discover What’s Hiding in Your Data with Exploratory Data Analysis - October 18

On-Line: 10:00 - 13:10 CEST | 09:00 - 12:10 BST

Join us online on 18 October!

We all use graphs to communicate data. But poorly designed, misleading graphs can do more harm than good. Data visualization – when done right – can transform not only the way you present results to colleagues and stakeholders in your organization, but also the way you explore and analyze the data itself. How can you be sure your visualizations add real value – not just noise?

In this seminar, data visualization guru Kaiser Fung will demonstrate how to:

Make effective visual displays.
Find a story in a raw data set.
Turn chart-making from a job requirement to a professional advantage.

About the Speakers

Kaiser Fung is the creator of Junk Charts, a leading blog on data visualization, as well as the author of two books on statistical thinking, Numbers Rule Your World and Numbersense. He was the founding director of the Master of Science in Applied Analytics at Columbia University and now runs Principal Analytics Prep, affiliate of the Harvard Business School Startup Studio in New York City.

Malcolm Moore, PhD, is JMP European Technical Manager. An expert in design of experiments, Moore worked at Light Pharma, BBN and Astra Zeneca and lectured in medical statistics at Newcastle University prior to joining JMP.

»Register to join us On-Line

Using Design of Experiments To Increase Predictability, Optimise Processes and Minimise Costs - October 18

On-Line: 14:30 pm - 16:40 CEST | 13:30 - 15:40 BST

Statistically designed experiments, otherwise known as DOE, is an invaluable tool for anyone looking to improve research, development and manufacturing processes and products in almost any industry. They can allow you to gain new and vital understanding that is just not possible using passively collected data, reducing costs and time to market and increasing quality.

But commonly used DOE methods can have limitations when applying them to many practical situations, and making use of prior data can be complicated because this data is messy and incomplete. This leads to inefficiencies, the failure to recognize the expected benefits, and the risk of low adoption of DOE itself.

You will learn how to avoid these pitfalls using the modern approaches to design and analysis.

About the Speakers

Damien Perret, PhD, is a research and development scientist at the French Atomic Energy Commission (CEA) where he works on glass formulations for high-level nuclear waste conditioning. Prior to joining the CEA, Perret worked on photoresist materials as a scientist at Rohm and Haas Electronic Materials. In 2003, he received a PhD in materials science.

Malcolm Moore, PhD, is JMP European Technical Manager. An expert in design of experiments, Moore worked at Light Pharma, BBN and Astra Zeneca and lectured in medical statistics at Newcastle University prior to joining JMP.

»Register to join On-Line

Please feel free to forward this invitation to your colleagues and others in your organization. When you attend with your co-workers, the whole team benefits. And even if you can’t make it, perhaps one of you colleagues can.

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