實驗設計 (DOE)入門:經典篩選設計與全因子設計
實驗設計(DOE) 常應用在醫療、生技製藥及高科技製造等產業,做為降低實驗次數及成本的一種方法,在進行實驗設計時有哪些重要原則與步驟?傳統實驗方法中的經典篩選設計與全因子設計的概念與應用有哪些?本篇文章將介紹DOE基本原則、經典篩選設計與全因子設計方法的概念與應用案例。
實驗設計(DOE) 常應用在醫療、生技製藥及高科技製造等產業,做為降低實驗次數及成本的一種方法,在進行實驗設計時有哪些重要原則與步驟?傳統實驗方法中的經典篩選設計與全因子設計的概念與應用有哪些?本篇文章將介紹DOE基本原則、經典篩選設計與全因子設計方法的概念與應用案例。
We are thrilled to invite you to take part in the pilot of the JMP Wish List Prioritization Survey, set to launch on July 3! Your feedback is invaluable as it will play a pivotal role in shaping the future of JMP by highlighting the ideas that hold the most significance to you.
Survey overview
Within this survey, you will be provided with 100 "coins" to allocate to your preferred ideas. You have...
JMP facilita el análisis de texto libre, y hace fácil usar código de fuente abierta mediante su integración con Python. Fácil, así como a mí me gusta. Siendo que también me gusta la comida Mexicana y el programa de YouTube De mi Rancho a Tu Cocina, decidí combinar mi amor por JMP y por la comida Mexicana en este blog. Para personas que no conocen a Doña Angela y su programa “De Mi Rancho a ...
Population studies are a fascinating subfield of genetics that focus on understanding genetic differences within and among populations to reveal a population’s genetic evolution. One of the key concepts that I focus on in this blog is examining population structure, in other words, analyzing genetic information across individuals originating from different parts of the world to see if JMP can cate...
Valerie_Nedbal
Julia O’Neill knows what it takes to speed life-saving treatments to market.
了解六標準差中的DMAIC方法,如何通過定義、測量、分析、改進和控制階段,幫助半導體行業實現持續改進產品質量。學習如何運用JMP工具進行統計分析和實驗設計,解決品質問題並優化製程。
The quest for Tour de France glory has driven cyclists to transcend the boundaries of human potential. Transcending those boundaries has led some cyclists down the unscrupulous path of winning at any cost. This blog looks at past winners – both scrupulous and unscrupulous – to determine if today’s cyclists can be trusted.
當今製造業的競爭激烈,企業需要不斷尋求創新的方法來提高效率、降低成本並保持產品品質。在這個動態且複雜的環境中,統計分析工具成為了業界的一大利器,而其中一個廣泛應用的工具就是決策樹。決策樹是一種強大的統計模型,能夠幫助製造業解決各種問題,從產品缺陷分析到生產效率優化,再到供應鏈管理和品質控制。在這篇文章中,我們將探討何謂決策樹,其有哪些應用場景與使用技巧,以應對日益變化的市場需求。
實現卓越製造是每個企業追求的目標。為了達到這個目標,品質部門必須不斷努⼒識別製程變化的來源,並採取適當的措施來控制⽬標。 透過數據分析理解製程⽣產過程,不僅可以增加⽣產的靈活性,⽽且能確保產品更好地符合客戶要求。如何基於科學的數據分析實現卓越製造,是每家企業都面臨到了難題,本篇文章就要透過應用工程統計的角度,分享如何透過SPC來減少品質管理中的製程變異。
You want to keep coding in JSL, but for a particular function, you know there's an easy way to write it in Python. So how do you create a JSL function that implements its functionality in Python?
The 2024 NFL draft is here and with it comes the madness of the draft day derby. This blog post covers the NFL draft, specifically focusing on the quarterback position. With as many as six quarterbacks projected to be picked in the first round, 2024 is shaping up to be one of the wildest NFL drafts in history. Looking at recent history, a QB drafted in the first round has less than a 50% chance o...
JMP Principal Systems Developer Paul Nelson spearheaded the effort to create a consistent, full-featured, integrated development environment for writing and executing Python scripts within JMP in JMP 18. The result? A more productive environment for Python developers that works immediately when installed, gives direct memory acces to Python data tables in a live environment, and an integrated Py...
Process analytical technology (PAT) is becoming increasingly important in the pharma industry, and other industries are starting to pick up on using PAT for their in-line, on-line, and at-line quality control measurements. For example, at the most recent European Discovery Summit, @Massimo Pampurini and @Sara Sorrentino, presented a poster on guaranteeing manufacturing process robustness by invest...
Hey there! You may remember me from my previous stint with JMP Statistical Discovery when I was a member of the Life Sciences group. Well, I’m back, and things are better than ever! Yes, they are. My return has generated a lot of questions both internal and external to JMP, but to answer the all-important question on why I returned to JMP, I first need to shed some light on why I decided to leave ...
JMP 18 introduces a lot of new capabilities, including revamped Python support, which allows users to directly access, modify, and create JMP data tables from Python. This is accomplished through the jmp.DataTable Python object. Keep reading to learn how to create a pandas.DataFrame from a JMP data table, as well as the reverse, a JMP data table from a pandas.DataFrame live and in-memory.
Applying a sample Platform Preset Making our own Platform Presets Managing your Platform Presets Exporting and sharing your Platform Presets Exporting presets to a file Creating an add-in with a bundle of Platform Presets Platform Presets pro tips Broadcasting Copy and paste platform settings Summing up I love efficiency, and one of the reasons I love JMP is that I can do so much in the software ...
Award-winning statistician Julia O’Neill presents at the JMP Explore biopharma event in Boston.
In component reliability, or non-repairable system reliability, we assume that after a component has failed, it is discarded and can’t be repaired. Lifetime of components is modeled using Weibull or lognormal distributions (among others), and the goal is to estimate the time that a given proportion of parts will have failed or the proportion of parts that will fail at a given time. In system re...