About ANOM for variances
Hi, I'm now studying the ANOM for variances. I don't understand why it needs at least three groups to start the comparison. Does anyone know the reason behind this? Thank you!
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view all learning resourcesHi, I'm now studying the ANOM for variances. I don't understand why it needs at least three groups to start the comparison. Does anyone know the reason behind this? Thank you!
Dear community, Just a quick question considering the formatting of the "No choice" option in JMP 17. If we have Option A, Option B, and Option C, where Option C = none of these options. Do we give three rows of data to JMP? Or would we give two rows of data in binary format, and when both option A = 0 and Option B =0, it will use this information that no option was selected? In the images below...
Hi Community,I created a 16 run RSM (Custom Design) with 1 categorical and 4 continuous factors. Early in the execution I was forced to change several factor levels for practical reasons. I restarted and completed all 16 runs at the new levels, recording on paper all the changes. When I updated the JMP run file and performed Analyze-Fit-Model, the model appeared to retain the previous factor level...
When I clicked Fit Model, "model 1" popped up, including "Random Block & Random" as a factor, which means "Random Block" is a Random rather than Fixed Effect. However, When I run "model 2" with just "Random Block" as a factor, everything becomes less efficient. Which is more correct and why? Also, I'm used to the Model 2 output, in which I can click on Scaled Estimates. And I was taught at a JMP t...
Hello,I am trying to compare the number of rejected units from 2 sample groups with unequal populations. I have read multiple times that the tool to use in JMP for that purpose is the "Fit Y by X", but it doesn't seem to take into account the population difference in my 2 groups (which I put in the Freq. box). How can I do my analysis? And how can I add more parameters to this analysis (I also wan...
Hi, I'm now studying the ANOM for variances. I don't understand why it needs at least three groups to start the comparison. Does anyone know the reason behind this? Thank you!
Dear community, Just a quick question considering the formatting of the "No choice" option in JMP 17. If we have Option A, Option B, and Option C, where Option C = none of these options. Do we give three rows of data to JMP? Or would we give two rows of data in binary format, and when both option A = 0 and Option B =0, it will use this information that no option was selected? In the images below...
Hi Community,I created a 16 run RSM (Custom Design) with 1 categorical and 4 continuous factors. Early in the execution I was forced to change several factor levels for practical reasons. I restarted and completed all 16 runs at the new levels, recording on paper all the changes. When I updated the JMP run file and performed Analyze-Fit-Model, the model appeared to retain the previous factor level...
When I clicked Fit Model, "model 1" popped up, including "Random Block & Random" as a factor, which means "Random Block" is a Random rather than Fixed Effect. However, When I run "model 2" with just "Random Block" as a factor, everything becomes less efficient. Which is more correct and why? Also, I'm used to the Model 2 output, in which I can click on Scaled Estimates. And I was taught at a JMP t...
I want to feed data as three sets: train, validation, and test set to jmp. how can I do this? does jmp use test set? or just training and validation?
Related to the previous post How to get "Effect size" column with Response Screening functionality , I am also wondering how effect size in the response screening platform is calculated, specifically for categorical Y vs continuous X. JMP help shows: "When Y is categorical and X is continuous, the effect size is the square root of the average ChiSquare value for the whole model test." Running b...
We want to rank the preference of population of animals for n different recipes. Recipes are tested in two-choice assays, where groups of over 100 individuals can choose one choice or the other. Preference for the group is computed as a preference index, a continuous variable that is between -1 and 1. Is there an experimental design that would help reduce the number of combinations to test in ord...
这是个异想天开的问题: 大家都说股票价格的未来走势预测是艺术、不是科学。
但我还是想看看JMP具体哪里模型能用于这方面。 我尝试过使用决策树、随机森林、xgboost。
还使用了DOE制作了均匀试验表来进行分类统计。
虽然这不是一个很好的问题、但还是非常期待专家们的回答。非常感谢!
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