Leading With Analytics: Fostering a Supportive Analytics CultureLeading With Analytics: Fostering a Supportive Analytics Culture
gail_massari
Racial Effect Analysis Using JMP in Supporting Drug Application for ST-101, A Fixed Dose Combination of Olmesartan and RosuvastatinWen Wang1, Larn Hwang1, and Vuong Trieu21Autotelic Inc, Fountain Valley, CA, USA; 2Stocosil Inc, City of Industry, CA, USAST-101 is a fixed dose combination (FDC) product of olmesartan medoxomil (OM) and rosuvastatin calcium (RC) for treatment of hypertension and hyper...
wwang_autotelic
Added Dimensions of Difficulty: Image Analysis and 3D Visualization in JMPThere is one constant in modern life. No, death and taxes don’t count. That constant is society’s desire for better performing and lower priced electronic widgets. It’s a first world problem to be sure, but most of us seem to have it. One of the results of this market demand is that semiconductor and MEMS manufacturing p...
MikeD_Anderson
Presented by Matthew Paul Goodlaw, California State University and New Mexico Public Education Department
gail_massari
Using Process Screening in JMP Pro to Analyze JMP JSL Testing Processes, Audrey Shull, Sr. Manager, JMP Development Testing
Audrey_Shull
JMP Pro 13 Modeling Workflow Enhancements with GenReg, Screen Predictors, and the new Formula DepotKaren Copeland, Boulder StatisticsBuilding models is often an exploratory, iterative process that can result in many saved models as one works to develop the most useful model for a particular application. The new Formula Depot in JMP13 Pro provides a workflow to save and compare models without clut...
KarenC
Melinda Thielbar, PhD, JMP Senior Research Statistician Developer, SASJMP 13 brings a host of new features for Choice modeling, including Maximum Difference analysis, options for modeling no-choice responses, a MaxDiff Designer, and improved features for market segmentation. This demonstration will cover how to use the new features, as well as the research behind the computations. We’ll use a case...
kathy_walker
New Features in Choice Modeling for JMP® and JMP® Pro 13Melinda Thielbar, JMP Senior Research Statistician Developer, SASJMP 13 brings a host of new features for Choice modeling, including a new Maximum Difference Analysis (MaxDiff) platform, and Hierarchical Bayes modeling in JMP Pro. Melinda Thielbar, the developer for the choice platforms, will discuss new features and how they benefit consumer...
melinda_thielba
If the data is non-negative, Non-negative Matrix Factorization can be used to cluster the observations, the variables, or both. By its nature, NMF clustering is focused on the large values. Our idea is to normalize the data, e.g. by subtracting the row/column means, and split the matrix into positive and negative parts. NMF clustering applied to the concatenated data, “PosNegNMF”, gives equal weig...
paulfogel
Editor's Note: This Poster was selected as the Best Student Poster for JMP Discovery Summit 2016.The objective of this project is to use image analysis in JMP to develop an automated program for extracting metrics from skin lesion images. This poster discusses two main aspects of image analysis in JMP: feature extraction (image processing) and data extraction (analysis of those features to create ...
juliagong
Editor's Note: This Poster was selected as the Best Student Poster for JMP Discovery Summit 2016.
Title: Influence of Motivational and Prevention Factors on Consumer Recycling BehaviorAuthors: Shaghayegh Rezaei, Kristin A. Thoney-Barletta, Jeffrey A. Joines, Lori RothenbergNorth Carolina State University
srezaei
Brian Corcoran BrianCorcoran, JMP Development Director (view in My Videos) In version 11, JMP Development introduced the Excel Wizard for the Windows product. This was followed by a version for the Mac in JMP 12. The feature has proven to be extremely popular, and the addition of a variety of new capabilities since version 11 makes it an appropriate time to revisit the Wizard...
kathy_walker
Chris Gotwalt chris.gotwalt1, PhD, JMP Director for Statistical Research and Development, SAS Clay Barker clay.barker, PhD, JMP Senior Research Statistician, SAS The Generalized Regression platform (GenReg) has evolved into a world-class framework for the analysis of designed experiments. In this presentation, we use simple case studies to demonstrate how easy it is to use GenReg's powerful new ...
kathy_walker
Scott Rubel scottrubel0, PhD, Senior Principal Engineer, NXP Semiconductors Todd Jacobs, PhD, Principal Engineer, NXP Semiconductors James Nelson txnelson, Software Engineer and Six Sigma Black Belt, Independent Contractor Introduction Modern chip designs have multiple IP components with different process, voltage, and temperature sensitivities. These components must all function across a wid...
kathy_walker
Jessica Behrle, Senior Principal Biostatistician, Janssen R&D Yinglei Li, PhD, Senior Biostatistician, Janssen R&DBarry Hogan, PhD, Senior Scientist, Janssen R&DYonghui Wang, PhD, Senior Scientist, Janssen R&DMichael Nedved, PhD, Associate Director, Janssen R&DFor process changes (site, scale, formulation, etc.) made to biopharmaceuticals (e.g., proteins, DNA, vaccines), comparability studies ...
kathy_walker
Jason Brinkley, PhD, Senior Researcher, American Institutes for Research Elizabeth Horner, PhD, Senior Researcher, American Institutes for Research (view in My Videos) Patterns of hospital utilization are multifaceted with causal mechanisms as diverse as patient populations. There is a need to identify patients with preventable high hospital utilization. Most research employs a direct mod...
kathy_walker
Bradley Novic, PhD, Principal Consultant, PhaseTwo AnalyticsMining manufacturing data can be a perilous endeavor from data assembly to analysis to interpretation and implementation of results. What sets data mining in manufacturing apart from data mining in, say, marketing or finance, is that prediction alone is not good enough in manufacturing. In manufacturing the end game is improved control, a...
kathy_walker
Sam Edgemon, Principal Technical Consultant, SAS Tony Cooper, PhD, Analytical Consultant, SAS Too often, the technical aspects of building models overshadow vital and foundational aspects of the process. This presentation focuses on important but often overlooked aspects of analytics: discovery, data quality, the presentation of analytical findings to management, deployment, the evaluation...
kathy_walker
Vishal Singh, PhD, Associate Professor of Marketing, New York University Qianyun (Poppy) Zhang, Research Assistant, New York UniversityThis talk focuses on text analytic capabilities of JMP 13 Text Explorer. We demonstrate the ease and capabilities of JMP 13 in analyzing textual data, and compare the results to popular text mining packages in R. The context of our study is online custome...
kathy_walker
David Lee, Director of Quality and Reliability, OLEDWorksEvery experiment yields multiple data types, each requiring unique analyses and controls due to the sub-micron nature of an innovative organic light-emitting diode (OLED). Three specific data methods will be discussed. First, the premise of the study centers on a six-factor definitive screening design that was built utilizing new features in...
kathy_walker
Jim Grayson jgrayson, PhD, Professor, Augusta University Mia Stephens mia.stephens , JMP Academic Ambassador, SAS Teaching business analytics to students has its challenges. But while students can typically develop an understanding of tools and techniques used in predictive modeling, they often struggle with communicating what they have learned and explaining the results in the language of the b...
kathy_walker
SPEEDING UP THE DIRTY WORK OF ANALYTICS Robert H. Carver rcarver , Professor of Business Administration Stonehill College, Easton MA 02357, (508-565-1130), rcarver@stonehill.edu and Senior Lecturer, Brandeis University International Business School, rcarver@brandeis.edu (view in My Videos) Abstract “Big data” is rarely ready for analysis when it arrives on your desktop. The issues are fami...
kathy_walker
Daniel Valente, PhD, JMP Senior Product Manager, SASJon Weisz, JMP Vice President of Sales and Marketing, SASAbstract JMP 13 introduces two new tools that make it easy for the analyst to deal with common data problems. Often two or more data tables are related by a common key, yet they are very different in terms of fact-sampling frequency or dimensions (e.g., long versus wide). Doing an actua...
kathy_walker
Ryan Lekivetz, PhD, JMP Senior Research Statistician Developer, SASThe Simulate Responses option in most design of experiments platforms is useful for generating simulated data for an experiment. In JMP 13, we have improved the response simulator by allowing for normal, Poisson and binomial distributed responses. We also create a column formula that generates the data. This feature is even more ef...
kathy_walker
Editor's Note: This paper was selected as the Best Invited Paper by the attendees of JMP Discovery Summit 2016. Heman Robinson heman.robinson, JMP Principal Software Developer, SAS HTML Version 5, or Interactive HTML, supports many of the exploratory features of JMP®, including point identification, linking, and brushing (Becker and Cleveland, 1987; Stuetzle, 1987). Saved reports can be u...
kathy_walker
kenneth_kovats