there is a sheer shortage of explanation videos related to advanced microeconomics....thankx for this wonderful one.....will b grateful to you foreva if you kindly consider to make videos on other topics too !
At 13:55, these two distributions are not possible right? Any pdf must sum to 1 so one distribution cannot be strictly less than the other (orelse that distribution sums to
Yes, sorry; the picture at this point is solely to indicate that they have the same mean but different variances. I should have drawn one with lesser amplitude.
Hi, your video is good, I am a student who has a weak mathematical background, I learn a lot, but when a notion like stochastic dominance comes, I still get confused on which math field this method belongs to, these high-end mathematical tools are really scattered in my mind like sands in the beach without any structural framework, which makes me frustrated when I want to use them. So, do you have any ideas to avoid this?
cumulative density function. That is, as the domain over which probabilities are calculated increases, every previous probability is added up. In discrete probability, it is basically the sum of all probability. In continuous case, it is simply the integral of the probability density function. We denote the cdf with big F and the pdf with small f, analogous to notations in calculus.
there is a sheer shortage of explanation videos related to advanced microeconomics....thankx for this wonderful one.....will b grateful to you foreva if you kindly consider to make videos on other topics too !
Crystal clear in concepts. Hope to watch some mathematical problems explained in future videos. Thanks very much indeed.
Love it. Thanks for the explanation!
I was literally looking for this topic everywhere. But, finally I got your video with detailed explanation of this topic. thankyou so much. :)
Wow. Really really intuitive explanation. Thank you.
Thank you very much David. Revising for an exam next week and this video has helped clarify the topic perfectly. Much appreciated.
Awwwsome video man.. Saved me a lot of time. Very well explained..
Thanks a ton for the video ! Wonderfully explained Sir.
Great video! Thank you so much. I was really struggling with the understanding of these concepts and this video helped to clarify that for me.
Thanks a lot, Professor Siegel!!
Very nicely explained, Thank you!
Cheers big fella, you seem like a top bloke
Thanks. Nice explanation.
This is gold! Thank you
Vaery good video, indeed. Great job ^^
Loved the explanation, cheers
Excellent video. Thank you. Btw your first example is zero-order dominant, even stronger than first-order.
Thanks sir.. Very good explanation.. Helped me a lot.
Really well explained, thanks.
Thanks a bunch! Really helped me out.
Amazing vid man, thanks so much
thank you very much sir for explain its really helpful....
Very helpful thank you. Is there a proof for if FOSD it is also SOSD and if SOSD does that guarantee FOSD, I am talking in case of the same mean.
Great video, thanks
I love you.
Thank you sir, got an exam in two days, you saved me!
thank you very much! it's VERY helpful!
Thank you!!
it helps a lot!! thank you so much!!
very helpful
At 13:55, these two distributions are not possible right? Any pdf must sum to 1 so one distribution cannot be strictly less than the other (orelse that distribution sums to
Yes, sorry; the picture at this point is solely to indicate that they have the same mean but different variances. I should have drawn one with lesser amplitude.
Very clear, thnx!
Very helpful thank you!
Thank you!
Hi, your video is good, I am a student who has a weak mathematical background, I learn a lot, but when a notion like stochastic dominance comes, I still get confused on which math field this method belongs to, these high-end mathematical tools are really scattered in my mind like sands in the beach without any structural framework, which makes me frustrated when I want to use them. So, do you have any ideas to avoid this?
I typically think of these topics as coming from a class in probability, but you might see them elsewhere as well.
@@DaveASiegel thanks, there are so many for me to learn.
Very god video! But can someone tell me what the CDF is he refers to? It might be a shortcut or i misunderstood it.
thanks in advance!
does it mean c.... density function. But what is the c?
cumulative density function. That is, as the domain over which probabilities are calculated increases, every previous probability is added up. In discrete probability, it is basically the sum of all probability. In continuous case, it is simply the integral of the probability density function. We denote the cdf with big F and the pdf with small f, analogous to notations in calculus.
Is the normally distributed function which you use during your second order stochastic dominance explanation a CDF?
Thanks
I just realized it can't be a CDF. I'm dumb. PDF?
sabsher117
Yes, it's a PDF. I think it's a little easier to convey the concept of a mean-preserving spread that way.
Yes, I finally got the hang of it. Thank you so much for your video. Much more helpful than my notes from lecture.
Thank you so much
thank you
Spoke too fast when explaining CDf and fosd; didn't make sense