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.
@richaneog82942 жыл бұрын
wonderful sir, couldn't understand but love your voice
@kikiy29723 жыл бұрын
This is the best JMP video I've watched! You're such a great instructor!
@mojtaba97673 жыл бұрын
Best JMP video that I found
@MIZRAIM19844 жыл бұрын
I wish all the teachers in tutorials were like you! I am amazed by your videos on JMP Pro!
@rachelcyr43063 жыл бұрын
You are amazing, this video has given me such an appirecation for JMP
@stuttigrit5 жыл бұрын
What a great demonstration / explanation and visualizations of how to perform multivariate analysis. Thanks!
@PatrickGiuliano6 жыл бұрын
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.
@RegularFellow255 жыл бұрын
amazing tutorial! I'm working with Jump and didn't know most of the tricks
@planaconsultoria2 жыл бұрын
This video was very well done! Thanks for sharing! Thinking about making something similar in other languages! 😁
@kiegh6 жыл бұрын
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!
@phillipr65966 жыл бұрын
Always positive reviews with you....
@kiegh6 жыл бұрын
nice...
@superuser86364 жыл бұрын
Great tutorial, thanks, Dr.!
@ThirdPlanetStudio Жыл бұрын
Great tutorial!
@JulianParrisPhD Жыл бұрын
Thank you, Tyler! I'm so glad it was helpful
@prettyscientist874 жыл бұрын
Wonderful tutorial. Very helpful thank you and I appreciate it.
@marcastro80523 жыл бұрын
Excellent. Thank you, sir.
@mau_lopez6 жыл бұрын
Great tutorial, fantastic explanation!
@vsandu Жыл бұрын
Brilliant, cheers!
@arnaudzida93476 жыл бұрын
Very helpful your tutorial, thanks
@javajoe47 ай бұрын
Is the dataset available for download? Would really be beneficial to follow along.
@Aesthetics10000 Жыл бұрын
How to do significane level test
@sawma3714 Жыл бұрын
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
@azizozturk26576 жыл бұрын
Great analysis thanks alot
@cliffordino6 жыл бұрын
Super helpful. Thanks.
@johnfox176 жыл бұрын
Thank you!
@Stephane17503 жыл бұрын
you sound like a young, optimistic Sam Harris! ;)
@hectorgomez93214 ай бұрын
hi James Covello
@hswn15 жыл бұрын
Thanks for the tutorial. Just a quick one, what does the pink area around the line-of-best-fit represent?
@JulianParrisPhD5 жыл бұрын
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
@hswn15 жыл бұрын
Julian Parris Thanks very much Julian
@rachelcyr43063 жыл бұрын
@Julian, would it be acceptable to use onehot encoded categorical variables?
@PatrickGiuliano2 жыл бұрын
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