Ordination using NMDS (Non-metric multidimensional scaling)

Ordination is a statistical technique used to simplify and extract the important patterns from complex ecological datasets. This video introduces the concept of ordination and then describes one of the most important techniques, non-metric multidimensional scaling.

[@Ingannoakagurzone]

the best NMDS explanation I have found

[@sau002]

I like the approach of beginning with an overview of the problem at hand, instead of jumping right away into the theory.

[@gavinaustin4474]

A simple, clear, to-the-point explanation. Thank you.

[@JamieBrewster]

An excellent video, thanks Rob!

[@Alexis-hn1yw]

thanks for the great explanation and the example! (examples are always more effective for understand a concept i think)

[@justinyow2057]

Never understood what was going on with NMDS until now. Great video

[@kmlee8408]

Best explanation ever

[@taaampie]

Thank you, thank you, thank you! You made my day :)

[@elaichahmed102]

Excellent présentation and easy to undresfand. BRAVO

[@JibHyourinmaru]

DAMN, YOU EXPLAINED IT SO NICELY. I get it now! thank you so much! subscribed!

[@cilie1140]

Thank you! Love the easy way of explaining this rather tricky technique:)

[@matsolsthoorn9590]

Mate, I never understood this and you've helped heaps! Thank you! :)

[@henny628]

Thank you for a very good explanation of NMDS is about.

[@flavianogueiradesa6634]

Excellent! Thank you so much for the easy explanation!

[@Jcakiiiii]

Such a great video! Thank you!!!

[@alfredoalarconyanez4896]

This was very well explained, thank you !!

[@atmospheric_blue]

Thank you so much for this!!! Just what I needed!

[@jennsimons4413]

What a well done video - thank you!

[@chelseajmw]

Bless you! This helps so much!!

[@betogracida]

Great explanation! Thanks!

[@omartovar7484]

amazing explanation! thanks!

[@indrecepukaite4276]

Great explanation, thank you!

[@johndorsett3967]

Very well explained... thank you!

[@jolittevillaruz5234]

great explaination

[@thandokazisam5981]

Well explained 👌

[@mcalencastro]

Perfect!

[@raselbarua4578]

nicely explained

[@DelphineLariviere]

How about the stress level from Power, J.F et al. (2018) , they have 2.2 , is it still a good representation ? Is it really informative in that case?
thanks!! , Great video!

[@user-ze7tl2dw4i]

It's 0.22

[@krikamoleno19]

What went inside ordihull () ? and points() ? I tried with ordi1 and I got error messages 😅

[@claudiocrespo4703]

I got a stress value of 0.21. So, what means my value? Thanks for your kind reply

[@farisayidakwa7024]

Thank you but i was asking were can i get the script for this example if you have please?

[@oceankat]

This is really useful!
I had one question - why would it be cause for concern if your stress plot has many points at 1.0, and what would be your method to overcome this? Thank you

[@tandindumbo5231]

sir can i have your email