Time in hh:mm but plots in seconds
I have time column with hh:mm data, however during analysis few plots show axis in seconds and few in hh:mm. How JMP decides what to use/display and how do I ensure output with consistent format?
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view all learning resourcesI have time column with hh:mm data, however during analysis few plots show axis in seconds and few in hh:mm. How JMP decides what to use/display and how do I ensure output with consistent format?
As the title states, I found differences in the result segments when performing density analysis. For example as the follows image, the orange data is not at a high point in "Compare of density", but it is the highest in "Composition of densities". Hope someone can help explain this reason, what is the operational difference between these two methods?
Hello, I ran a DOE on JMP 17, and I am beginning to parse the data with JMP using the effect summary. It is a four-component mixture. I've watched some videos in the JMP catalogue on using the effect summary for mixtures and been following what they've been doing (removing sources that had a P value >0.05, if it doesn't have any dependencies above it). Are there any circumstances, that I would dev...
I have a split plot design with A,B,C,D factor. C was used as blocking. D was assigned as uncontrolled.1. When analysed by the model script, R is coming as 1. I tried to reduce the model by removed higher order effects E.G A*B*C*D etc. In reduced model A is showing curvature effect with R of 0.93 and AIC of 174.2. I also analysed the response with full factorial effects and reduced higher order e...
JMP17
I have time column with hh:mm data, however during analysis few plots show axis in seconds and few in hh:mm. How JMP decides what to use/display and how do I ensure output with consistent format?
As the title states, I found differences in the result segments when performing density analysis. For example as the follows image, the orange data is not at a high point in "Compare of density", but it is the highest in "Composition of densities". Hope someone can help explain this reason, what is the operational difference between these two methods?
I have a split plot design with A,B,C,D factor. C was used as blocking. D was assigned as uncontrolled.1. When analysed by the model script, R is coming as 1. I tried to reduce the model by removed higher order effects E.G A*B*C*D etc. In reduced model A is showing curvature effect with R of 0.93 and AIC of 174.2. I also analysed the response with full factorial effects and reduced higher order e...
JMP17
Hallo.I have a DOE design with response data as a table, created starting from an Excel table. Here my DOE experiences:I can create a contour plot easily. The response column - as well as all factors X - are appearing in the lists for the corresponding variables and can be used for the plot. I practically get the same plot with OriginLab. If I want to obtain an analysis diagram or a contour an...
Hello, I am still new to JMP but I'm trying to determine the best way to model a non-linear system (generating DOE + model fitting). Context: Long story short, I have a large experimental space that I am trying to model (10 discrete variables + 10 continuous variables). Before I jump into my full experiment I'm working with a subset (1 discrete variable + 5 continuous variables) to make sure I'm m...
Hello! I appreciate your help in advance! I am currently trying to figure out the proper way to analyze my data! I had used the DOE feature of JMP to create this fraction factorial of 24 runs for m experiment. The goal is two screen which categories have the most effect on the success rate. I had initially use the response screening option to analyze my results, when I did that none of my values...
Hi everyone, I'm currently engaged in a process development project with the goal of 1) minimizing the total process time while 2) maintaining or enhancing the yield. This objective is similar to viral vector production case, where maximizing virus yield in the shortest production time is crucial. After consulting with subject matter experts, we've pinpointed 10 factors for potential modification....
If you have are making a design with a factor you are certain will have a quadratic relationship against a response but you have a wide range, can it be helpful to define a 3rd order model effect for that factor to better identify and model curvature. I work in purification and we often deal with a recovery vs. purity balance. This relationship is usually quadratic around the optimal, where at a l...
Hello community!!A query:- How JMP is configured to generate neural networks that learn from their inputs in real time (incremental learning) in such a way that it continually updates its weights according to new inputs and generates updated real-time predictions.Greetings,Marco
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