I become very happy from biometrics analysis in jmp,so researchers should be keep it up to find world problem solver technology system for un solved problem.
Fantastic tutorial Julian, I'd love to see you expand on some of the methods you highlighted and introduced @ the end of this video (Heirarchical Clustering, Latent Class, Principal Components) in a separate video.
Hi there. Thanks for this wonderful explanation of how to use JMP. I am very thankful for your explanations and I look forward to learning more from you about this tool!
What if a data has a lower end and an upper end value which should be treated as one unit vs another unit? For example: Min temperature and max temperature of a water vs fish population or such
Hi Saad -- that shaded region is the confidence region. Like a confidence interval for a point estimate (like a mean), the confidence region or confidence band is a representation of uncertainty about where that linear relationship is in the population from which the current sample was drawn. In other words, the different lines that could be in that region all reflect reasonable candidates for the true relationship between the Y and X variables. Here's the link to the wikipedia page for more information: en.wikipedia.org/wiki/Confidence_and_prediction_bands
I think you can use one-hot encoded categorical variables but in general it's best to really pay attention to both your data type and modeling type in JMP! There is a reason why these two pieces of metadata are so important for each column [and are the first two column properties you see for every column in JMP] because they tell JMP which models are appropriate for your particular data situation (graphs/analyses that are not appropriate will not be selectable in JMP's workflow). For those that are unfamiliar with one-hot encoding here is a good intro read: www.educative.io/blog/one-hot-encoding#what
wonderful sir, couldn't understand but love your voice
Best JMP video that I found
I become very happy from biometrics analysis in jmp,so researchers should be keep it up to find world problem solver technology system for un solved problem.
This is the best JMP video I've watched! You're such a great instructor!
What a great demonstration / explanation and visualizations of how to perform multivariate analysis. Thanks!
You are amazing, this video has given me such an appirecation for JMP
I wish all the teachers in tutorials were like you! I am amazed by your videos on JMP Pro!
Fantastic tutorial Julian, I'd love to see you expand on some of the methods you highlighted and introduced @ the end of this video (Heirarchical Clustering, Latent Class, Principal Components) in a separate video.
This video was very well done! Thanks for sharing! Thinking about making something similar in other languages! 😁
amazing tutorial! I'm working with Jump and didn't know most of the tricks
Hi there. Thanks for this wonderful explanation of how to use JMP. I am very thankful for your explanations and I look forward to learning more from you about this tool!
Always positive reviews with you....
nice...
Wonderful tutorial. Very helpful thank you and I appreciate it.
Great tutorial, thanks, Dr.!
Great tutorial, fantastic explanation!
Great tutorial!
Thank you, Tyler! I'm so glad it was helpful
Excellent. Thank you, sir.
Very helpful your tutorial, thanks
Brilliant, cheers!
Is the dataset available for download? Would really be beneficial to follow along.
Super helpful. Thanks.
Great analysis thanks alot
What if a data has a lower end and an upper end value which should be treated as one unit vs another unit? For example: Min temperature and max temperature of a water vs fish population or such
Thanks for the tutorial. Just a quick one, what does the pink area around the line-of-best-fit represent?
Hi Saad -- that shaded region is the confidence region. Like a confidence interval for a point estimate (like a mean), the confidence region or confidence band is a representation of uncertainty about where that linear relationship is in the population from which the current sample was drawn. In other words, the different lines that could be in that region all reflect reasonable candidates for the true relationship between the Y and X variables. Here's the link to the wikipedia page for more information: en.wikipedia.org/wiki/Confidence_and_prediction_bands
Julian Parris Thanks very much Julian
Thank you!
you sound like a young, optimistic Sam Harris! ;)
How to do significane level test
hi James Covello
@Julian, would it be acceptable to use onehot encoded categorical variables?
I think you can use one-hot encoded categorical variables but in general it's best to really pay attention to both your data type and modeling type in JMP! There is a reason why these two pieces of metadata are so important for each column [and are the first two column properties you see for every column in JMP] because they tell JMP which models are appropriate for your particular data situation (graphs/analyses that are not appropriate will not be selectable in JMP's workflow). For those that are unfamiliar with one-hot encoding here is a good intro read: www.educative.io/blog/one-hot-encoding#what