Probability functions: pdf, CDF and inverse CDF (FRM T2-1)
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- Опубліковано 29 вер 2024
- [Here is my XLS @ trtl.bz/2AgvfRo] A function is a viable probability function if it has a valid CDF (i.e., is bounded by zero and one) which is the integral of the probability density function (pdf). The inverse CDF (aka, quantile function) returns the quantile associated with a probability, q = F^(-1)(p), whereas the CDF returns the probability associated with a quantile: p = F(q). As mentioned, the =POISSON_INV(.) is not built into excel. Rather, it is available from the wonderful and free add-on published by Charles Zaiontz and available at www.real-statis.... Discuss this video here in our FRM forum: trtl.bz/2O7chQg.
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great video.i learned a lot from it.i would like to know what work do u do and where?
Thank you for watching! Bionic Turtle is an FRM study prep program. We provide study materials for the FRM exam on our website www.bionicturtle.com
You teach better than some professors in the university.
Is there a formula to obtain the CDF directly when SD=1 and mean=0?
Just wondering if there’s a way besides the “=NORM.S.DIST(XX,TRUE)”
Thank you..
BTW, Thanks for sharing the knowledge.
Nice video and good explanation but a bit lengthy and too much of repeating
okay i appreciate the constructive feedback, thank you
Really easy to understand
Thank you! We always appreciate this kind of feedback!
Brilliantly explained.
oh gosh thank you!
Great video! Would love to see you do a similar video using lognormal distribution .... thanks!
Thanks for sharing. it was very useful for me.
Thank you for watching!
Great presentation and thanks for sharing it.
Thank you for the support!
Count vs Measured. Thanks a lot.
how to calculate N'(d)
Thanks so much for sharing
Great example, I understand this concept well. Thanks!
Thank you for watching!
Thanks for sharing it!!
Thank you for watching!
Is it really true when we ask the probability for an interval from CDF not PDF ?
as i'm sure you know, for a continuous distribution P{a < X < b) = integral [a,b] of the f(x) pdf, or equivalently, F(b) - F(a) of the CDF
Yes right.
good one but y cant you do problems involving temperature, strings and time intervals too