常見的實驗設計流程?9分鐘快速了解JMP DOE優勢
常常聽到JMP的實驗設計(DOE)很好用,但是與其他軟體比較起來贏在哪裡呢?今天就從實驗設計流程開始,一一介紹DOE在不同實驗設計流程中脫穎而出的亮點為何。
常常聽到JMP的實驗設計(DOE)很好用,但是與其他軟體比較起來贏在哪裡呢?今天就從實驗設計流程開始,一一介紹DOE在不同實驗設計流程中脫穎而出的亮點為何。
Experts share the why and the how of green chemistry. Watch our Green Chemistry event on demand anytime.
Experts explain how these topics come together to make the world a better place. Join us for an event that is relevant to everyone, since we all use products make from chemicals.
Do you have large datasets that contain many input variables…maybe dozens or even hundreds of input variables!? JMP's Predictor Screening platform allows you to quickly determine which of these large number of candidates are the most significant in their ability to predict an outcome!
Just look at the list of Character functions available in the JMP Formula Editor. Not that anyone is counting, but that's 42 functions! Needless to say, if you've got a character column and want to change it somehow, JMP probably has a function to do it for you. Notice, though, that nine of those functions are all – or mostly – about extracting some portion of a character value. Admittedly,...
It should not take minutes to extract summary statistics! Learn how to extract any desired summary statistics for as many variables as you want in a matter of seconds!
Too many rows of data clouding your discoveries? Do you only want to focus on a very specific subset of your data? Learn how to filter and extract your desired data in a matter of seconds!
Phil Kay explains why OFAT is such a waste of time and effort.
Following his plenary talk at Discovery Summit, the filmmaker and naturalist answered questions from viewers.
Does a mix of stocks and bonds circumvent the drawbacks of the previous two approaches?
在進行研究時,很多研究人員會思考一個問題:「我取的樣本數足夠嗎?」由於樣本數會直接影響到研究的嚴謹性及研究結論的可靠性。當樣本數太小時,研究結果不穩定,得到「假陰性」結果的風險也大;當樣本數太大,又會增加研究成本和實驗難度。 到底該如何確定研究的樣本數是否合理呢?今天JMP就要來介紹如何透過Power analysis去取得合適的樣本數。
Join us for our World Water Day Cleanup activity. Clean up litter around your home and let us analyze the data.
We are already to the halfway point of Discovery Summit Europe, but there is so much more in store for 22 and 24 March!
電子製造業的零件尺寸較小、生産周期較短,使得設備及産品的異常診斷能力變得非常重要,其辨識能力的強弱甚至成爲了企業競爭力的一部分。如何快速、高效地識別這些異常,以及做好提前預警和分析,是提高良率不可或缺的一大環節。 今天我們以高科技中的案例爲例,來看看如何透過JMP強大的神經網絡建模與資料視覺化,幫助數據分析人員大幅减少異常芯片的識別與偵測時間,幫助企業提高生產效率與品質。
相關分析,是常見的統計分析方法,目的是在研究兩個或多個變量之間是否存在某種相關性,該如何判斷變量之間的相關性為正還是負?如何使用JMP中進行相關分析?今天的文章我們就來一起探索相關分析,包含Pearson相關、Spearman相關以及偏相關。
We’re excited that Discovery Summit Europe is here. We hope you are, too!
We had so many great questions from our Statistically Speaking audience.
We’re less than one month away from JMP Discovery Summit Europe 2022.
For International Day of Women and Girls in Science, I asked JMP colleagues who studied and worked in various STEM fields -- and who are all agents of change in their own ways -- this question: In your experience, what will it take to achieve gender equality in science? Here are their responses. Laura Castro-Schilo with her daughter at a conference