More on the many advantages of structural equation models
Ken Bollen: The many advantages of structural equation models
Ken Bollen: The many advantages of structural equation models
UPDATE: The results are in. See some of the interesting results on JMP Public. Watch the video announcing and hearing from the winners. To celebrate JMP’s partnership with telemetry expert and MotoGP Performance Engineer Mirco Bartolozzi, we invite you to sign up for a veritable data visualization grand prix. Use JMP with real motorsport data to uncover the complexity of this real-world challenge...
Monoclonal antibodies (mAbs) have transformed the therapeutic landscape, offering targeted treatments for cancer, autoimmune disorders, and rare genetic diseases. Unlike small molecules, mAbs are large, highly specific proteins that bind precisely to disease-associated targets, minimizing off-target effects and improving patient outcomes. In the biopharmaceutical industry, Chinese Hamster Ovary (C...
Last summer, we launched a pilot version of the JMP Wish List Prioritization Survey to explore a new way of gathering and prioritizing the incredible ideas submitted by our community. The response was fantastic – and we’re excited to bring it back this year! You can participate in this year's survey using this link. We encourage you to share it with your friends and colleagues as well!
What we lea...
Testing your JSL scripts just got a whole lot easier. We’ve built an implementation of Hamcrest for JSL, designed to help you write tests that are both powerful and easy to understand, complete with informative failure messages. With this add-in, you spot issues faster and improve your JSL more efficiently. Justin Chilton (@Justin_Chilton) and I developed a JSL-Hamcrest add-in that brings the flex...
JMP is a wizard at importing data from Microsoft Excel!
This is my favorite example for explaining a key difference between PCA and EFA.
“One-factor-at-a-time is scientific junk food,” says scientist, statistician, and author Dennis Lendrem.
Anytime there is interest in exploring group differences, multiple-group analysis (MGA) can be a helpful tool. Differences in means, regressions, loadings, variances, and covariances of variables can be investigated using MGA, as all these parameters can be modeled in the structural equation modeling framework.
Watch the video below to see how the fictional company Helios uses JMP Live to manage all aspects of its business. The case study uses a sample quality problem to show how automated report refresh, tools, and dashboards in JMP Live allow the entire organization to see, solve, and manage problems together. This high-level video focuses on the day-to-day use of JMP Live. (view in My Videos)
Dennis Lendrem’s LinkedIn newsletter, Apes in Lab Coats, has spawned two books.
Since its launch in October 2024, the JMP Marketplace has served as a central hub for secure, quality-controlled JMP extensions. To offer you the best possible experience, we're streamlining our platforms and phasing out the File Exchange.
"I’m not tech savvy. I just don’t get math. It’s like a foreign language. I can’t do this." - Kirsten Boyd, Newburyport High School
Our popular Statistical Thinking for Industrial Problem Solving (STIPS) course, which is hosted by our colleagues in SAS Education, is being transitioned to the new SAS learning platform.
The Monty Hall problem is a fun and seemingly paradoxical thought experiment that has confounded many smart people. It happens to be fairly straightforward to solve using JMP, and it presents an opportunity to learn a little about column formulas at the same time. Read on to learn more.
A compelling component of presenting research is graphs of data collected and the story those visualizations tell. The Graphs for the Experimenter add-in helps JMP users in the life sciences create visualizations in Graph Builder. The add-in offers templates for commonly used analyses and gives researchers a start with using graphs to explore data and share discoveries. Watch the video below to ...
在智慧製造與精益轉型的浪潮下,產品與系統的「可靠度」早已不再是傳統的品質管控指標,而是影響客戶滿意度、品牌信任與運營效率的核心競爭力。從消費電子、汽車零部件,到工業設備與半導體產品,可靠度分析正快速成為工程團隊不可或缺的關鍵能力。 可靠度是指產品在特定時間和使用條件下無故障運行的能力。從資料分析的角度出發,我們通常會通過「壽命分佈模型」來描述產品的失效時間分佈,其中最常見的是 Weibull分佈,它可以精準描繪不同時間點的失效率與風險函數。
在半導體產業的工作生態中,常常需要對面對的不良狀況找出問題來源,迅速地導入改善對策,而其中最為困難的階段是如何快速地從動輒上百上千的參數中,尋找出最相關的影響因子。以往,可能只能依靠工程師的過往經驗,慢慢的對懷疑的參數試錯找出關鍵因子,這樣的方式不僅耗時曠日,也可能忽略其中重要的指標。如何快速找到製程可以優化的方向,絕對是每一個工程團隊所面臨的一大挑戰。
Learn about how JMP users from notable organizations explore data and overcome obstacles. See and read presentations from over 55 JMP Discovery Summits.