Anne oversees analytic strategy in JMP Product Marketing. She is a contributing faculty member for the International Institute of Analytics. She enjoys organic gardening and spending time with her family.
Galit Shmueli, National Tsing Hua University’s Distinguished Professor of Service Science, will be visiting the SAS campus this month for an interview for an Analytically Speaking webcast. Her research interests span a number of interesting topics, most notably her acclaimed research, To Explain or Predict, as well as noteworthy research
Popular xkcd comic and author, Randall Munroe, delivered a fantastic closing plenary, Complicated Stuff in Simple Words, at JMP Discovery Summit last month. Based on his very popular second book, Thing Explainer: Complicated Stuff in Simple Words, it was hugely entertaining, and we are sharing it as this month’s episode of
Clay Barker has been busy extending the usefulness of the Generalized Regression platform in JMP Pro, adding many new models and enhancing ease of use. Generalized Regression (or GenReg for short) debuted in JMP Pro 11 as the place to do a trio of popular penalized regression techniques: Lasso, Elastic
Building on the new features in JMP 13 for exploring unstructured text data, JMP Pro 13 enables you to do more with text data, like cluster terms and phrases and use text in predictive models. You’ll be able to answer more questions, scale to larger data and stay in flow.
From time to time, the addition of new features requires a review of how capabilities are organized and presented in JMP. Are they located where it makes the most sense and where users would expect to find them? For example, in JMP 12 there was enough new material combined with
JMP users might notice that new versions of the software often bring the ability to support new kinds of data. The ability to incorporate image data came with JMP 12, and with JMP 13 comes support for text data. In the early days of this platform’s development, we were brainstorming
MaxDiff (maximum difference scaling) is a new platform in JMP 13 that will be helpful to anyone who does consumer research. It enables a specialized type of choice model where respondents are asked to evaluate items (product attributes, …) in sets of three to five, choosing the most preferred and least
Have you ever wanted to include data in an analysis without having to subset it from different tables and put it all together in a new table? Have you wanted to “see” how your data will come together before committing to joining many tables to make sure you get it
Heath Rushing is someone I count myself very fortunate to know — first as a colleague at SAS and now as co-founder of Adsurgo, a successful consultancy. Over years of JMP use, Heath has enthusiastically taught classes using JMP, written papers and the book, Design and Analysis of Experiments by
Dr. Karen Copeland will be our featured guest on Analytically Speaking on June 8. She is the owner of Boulder Statistics, a successful consultancy to a wide array of industry sectors around the world — medical device, diagnostics, chemicals, marketing, environmental, consumer and food products, pharmaceuticals, and web analytics, among