Calibration Curves 101 (UPDATED)

In this video, we will be talking about calibration curves! We will demonstrate how to inject a known set of standards and using it to compare the unknown sample.
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[@paulocambranis5109]

My god, this video is better than a whole virtual semester on analytical chemistry, please, please, keep this up

[@minnoq4047]

I laughed and learned. Best teacher I ever met! Thank you for making science easy but that you don't show it as being perfect.. because it is not :)

[@carolinacolombotedesco1172]

So funny and great! Thanks for the awesome work!!

[@DavidYazdi1]

Our pleasure!

[@RoyalKing-fi3gd]

I don’t know what you have done but I enjoyed it☺️🙃😂♥️

[@nubiamora5553]

I love it

[@aliciaganas2785]

thank you for this

[@DavidYazdi1]

You're very welcome!

[@tahaazhdari2876]

Tnx this video was very useful What was the solute?

[@julianewhouseful]

love

[@alexfitzpatrick2421]

This is excellent ty for saving my bacon

[@chemistmcg]

need some quantitative transfer technique in there to make sure that anything in the weigh boat makes it into the stock flask.

[@miniman809]

Can you please do a video about starting up and running HPLC samples? I'm scared of this instrument.

[@DavidYazdi1]

That would be a great video. What all would you want to see in a video like that?

[@miniman809]

@@DavidYazdi1 How do I stabilize the instrument? One time some of my peaks were on the next sample's chromatogram, WTH? Best practices and hacks?

[@cardoondemand]

You’re so funny 🤣🤣🤣

[@DavidYazdi1]

Glad you enjoyed it!

[@mrs.noulhaq1036]

What is R square???

[@thriyampakandhivyakrishnan2434]

I am not absolutely sure but R would be the product moment correlation. The product moment correlation is a measure of the correlation of two variables X and Y measured.

[@katieplatek9906]

in simpler terms, its a way of knowing how "accurate" your data points are. If r^2 is closer to 1, that means your points are falling on that linear line (Cal Curve). 1=100% of your points are falling on your calibration curve line. So an r^2 value of say 0.9998 is very accurate. The closer your r^2 value is to 0, the less accurate your data points are. So and r^2 value of 0.9281 is less accurate to you cal curve. I've attached a video that helps explain the theory a little better and its easy to understand (probably better than I did) kzbin.info/www/bejne/fabSaKGqjqasf7s