1. R

    Probability - Conditional Independence

    @David Harper CFA FRM , can you please share an example of the below case if possible? Events can be conditionally independent yet unconditionally dependent. Events can be conditionally dependent, yet independent! [Chapter 1: Fundamentals of Probability, Study Notes, Pg. 5] It will be easy to...
  2. P

    Miller chapter 3

    How will we solve the same by problem by using 70 and 30 percent probability sum by taking probailiy 70 and 30
  3. P


    What is empirical probability if we roll a dice once what is the probability of receiving 3 on a dice (ans 18%)?
  4. Nicole Seaman

    CFA Level 1 CFA: Correlation, covariance and probability topics

    Session 2, Reading 9 (Part 2): This video reviews portfolio variance and covariance, where covariance is the expected cross-product. We look at correlation, which is given by the covariance divided by the product of standard deviations, and therefore standardizes the covariance into a unitless...
  5. G

    Rating Migration Matrix

    Hello Can anybody help to guide how to answer these questions? Thank you. Edited by Nicole to include questions (please include questions in text format instead of an attachment): 1 What is the probability that a firm rated A will default in 1 year? 2 What is the...
  6. C

    New to the Forum - simple variance question

    How is the variance calculated? I'm sort of stuck on this problem, although I was able to understand it during the 6-sided die example. Thanks for any help!
  7. S


    Hi David, Apologies if this question is non-sensible or has been asked already (please tag a link if this question has been asked) but I just started preparing for an exam and I have one question so I know what to expect when I am learning it. Integration and calculus sort of questions as far as...
  8. Nicole Seaman

    YouTube T2-1 Probability functions: pdf, CDF and inverse CDF

    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...
  9. Nicole Seaman

    P1.T2.708. Probability function fundamentals (Miller Ch. 2)

    Learning objectives: Describe and distinguish between continuous and discrete random variables. Define and distinguish between the probability density function, the cumulative distribution function, and the inverse cumulative distribution function. Calculate the probability of an event given a...
  10. J

    Completely Lost in Quant

    Hello, I am sure this has been addressed before but I have searched everywhere and really couldnt find the exact answer I am looking for. I just started the Quant book, from GARP, and by page 20 I am already pretty lost. I understand the basic concepts covered up to that point (probability...