| Segment | Description | Who's On Air |
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Welcome |
The Monologue | |
| Featured Program |
Meet the Author: Doug and Brad In this episode of Meet the Author, Anne Milley interviews world-renowned DOE experts Doug Montgomery (Arizona State University) and Bradley Jones (JMP). Ten years in the making, their recently published book, Design of Experiments: A Modern Approach takes a new look at the powerful data analysis tool. Unlike many DOE textbooks, Montgomery and Jones’ doesn’t focus on the technical or mathematical parts of experimental design, but on the critical tasks of planning and designing your experiment. Every chapter starts with a “textbook design” experiment, included to show how important a thoughtful design is in conducting a successful experimental design effort. Though not the focus of the book, JMP is featured for many of the design and analysis discussed.
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@bradleyjones |
| Resource Spotlight |
“You never know what you can do until you try, and very few try unless they have to.” Mastering JMP host Gail Massari introduces this popular webinar series designed to show users how to solve common analytics problems. Free, live and interactive, these webinars give you a chance to see JMP in action. To better describe the series, Gail is joined by a couple of regular attendees – Amy Phillips from Proctor & Gamble and Tom Bidwell INEOS Composites. In addition to hearing why they’re such big fans of the series, Amy and Tom tell you how they use insight from these talks to advance their organizations and expand the knowledge of their colleagues. (BTW, livestream events are provided on demand, for those who cannot attend in person.)
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@gail_massari |
| Ask the Data Doctor |
Data Doctor Brady Brady shows you some of the cool, built-in, point-and-click functions you’ll find in the Columns Menu (Cols) of JMP. You’ll learn how to convert text to columns and how to break up text or numerical data found in a single column and transform it into multiple columns for better clarity or insight. As an example, Brady shows us how to convert a column that includes first and last names into multiple columns that separate out first, middle and last names. (Phone numbers, emails, etc., can be done in the same way.) Best of all, Brady shows you how to repeat the process formulaically, using the Words, Word and Eval Insert functions in JMP.
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@brady_brady |
| Mindful Moment |
See what you notice when you scan your body from head to foot.
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@arati_mejdal |
| Featured Program |
Forecasting Made Easier and Faster Yogi Berra famously said, “It’s tough to make predictions, especially about the future.” Clearly, Yogi didn’t use JMP. In this presentation, Jian Cao shows you the new time series forecasting platform introduced in JMP 15. Simple to use, easy to set up and fast, JMP can fit up to 30 models and select the best one for forecasting, using two types of error, five types of trend and three seasonality types. After introducing state space smoothing models to make forecasting easier, Jian uses sample data and JMP Pro to demonstrate the concepts he shares in his talk. At the conclusion of his talk, Jian shows the forecasting that is available in Graph Builder as well.
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@jiancao |
| Stat Snacks |
In today’s Stat Snack, JMP Systems Engineer Jeff Upton gives us a beginner-friendly crash course on Multiple Linear Regression. Using the Prediction Profiler, Jeff shows you how JMP can take multiple variables and predict how factors will change as you adjust different variables.
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@Jeff_Upton |
| JMP in Action |
See JMP’s Multiple Factor Analysis (MFA) in action. Using a dataset on wine ratings, JMP’s Olivia Lippincott shows you how you can specify “column blocks” to easily identify outliers (in this case, outlier “expert panelist ratings”) and generate a Consensus Map to further examine variation in our data. Once identified, Oliva shows you an example of a sensory analysis technique to find groupings of similar products and identify outlier panelists.
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@O_Lippincott |
| Tip of the Day |
In this episode of Tip of the day, Pete and Mary are back to walk us through hiding and excluding rows, and how to use the special Row State data type to store attributes like color, marker and other row state information. If you spend time coloring, marking, selecting, or excluding rows and want to make sure they are saved for later use, you’ll learn a lot from this ToTD.
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@Peter_Hersh |
| Closing | The Last 5 | @julian |