Thank you very much! our prof started right away explaining it in 3 dimensions /using indifference curves and therefore I was a bit lost. Thanks a lot!
This is the first time I get the reasoning behind quasi-concavity and quasi-convexity. Thank you so much! I'm looking forward for another videos of yours!
So I do now have a bit better understanding of the definitions, but am still a bit confused regarding the following With the given definitions, the function you initially use to show quasiconvexity from 10:00 onwards, appears to also fulfil the definition for quasiconcavity, as f(x) (Which would be the Min{f(x), f(y)}) would always be lower than f(xLambda + (1-Lambda)y). Does this mean certain functions can be quasiconcave and quasiconvex at the same time? If we would now take a simple linear function f(x) = x, both the conditions for quasiconcavity and quasiconvexity would be met for any x,y combination and any Lambda [0,1], right?
Yes, quasilinear functions can be both quasiconvex and quasiconcave. Test the stronger definition for just convexity and concavity on the simple linear function you defined i.e. f(x) = x. A linear function is both convex and concave. The same intuition is behind quasilinear functions.
Thank you very much! our prof started right away explaining it in 3 dimensions /using indifference curves and therefore I was a bit lost. Thanks a lot!
Well appreciate your videos, really helping me with Advanced Micro!
This is the first time I get the reasoning behind quasi-concavity and quasi-convexity. Thank you so much! I'm looking forward for another videos of yours!
Your videos are awesome. The way you explain things are so clear. You are seriously saving lives:)
So I do now have a bit better understanding of the definitions, but am still a bit confused regarding the following
With the given definitions, the function you initially use to show quasiconvexity from 10:00 onwards, appears to also fulfil the definition for quasiconcavity, as f(x) (Which would be the Min{f(x), f(y)}) would always be lower than f(xLambda + (1-Lambda)y).
Does this mean certain functions can be quasiconcave and quasiconvex at the same time?
If we would now take a simple linear function f(x) = x, both the conditions for quasiconcavity and quasiconvexity would be met for any x,y combination and any Lambda [0,1], right?
Yes, quasilinear functions can be both quasiconvex and quasiconcave. Test the stronger definition for just convexity and concavity on the simple linear function you defined i.e.
f(x) = x.
A linear function is both convex and concave. The same intuition is behind quasilinear functions.
Very well and very clearly explained. Thank you!
THANK YOU LOVELY EXPLANATION NOW I UNDERSTAND THE LOGIC PART OF IT . SUBSCRIBED AND WILL LOOKING FOR FUTHER VIDEOS
Teaching Brilliance peaked !!
great explaination super helpful!
Thanks, this was really helpful!
Thank you so much Sir for this marvelous video. I'm sorry Sir if you don't mind is there a way for Subtitle in English Sir not auto generated one?
very helpful
Thank you for your video, but you could have explained it in a shorter video. You just repeated again and again same sentences and same concept
really helpful, thanks!
Are any relative textbooks recommended?
Very good demonstration, thank you
Thank you very much from Italyyyy
A Genuinely amazing video
I love you Man
Good explanation!
You are the best