Learning objectives: Calculate the probability of an event for a discrete probability function. Define and calculate a conditional probability. Distinguish between conditional and unconditional probabilities. Explain and apply Bayes’ rule.
Questions:
20.2.1. The probability graph below...
In terms of this CFA playlist, we are still in the early quantitative methods or the foundations of quantitative methods. In the previous video, I reviewed some basic statistical concepts and now I follow that up with a review of some basic or foundational probability concepts. We want to hit...
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!
Variables are independent if and only if (iff) their JOINT probability is equal to the product of their unconditional (aka, marginal) probabilities; i.e., if and only if Prob(X,Y) = Prob(X)*Prob(Y). Further, if variables are independent then their covariance (and correlation) is equal to zero...
The probability matrix includes joint probabilities on the "inside" and unconditional (aka, marginal) probabilities on the outside. The key relationship is joint probability = unconditional * conditional.
Here is David's XLS: https://www.dropbox.com/s/thqkesz65niutil/1204-yt-probability-matrix.xlsx
Hi I was trying to understand the difference between Joint Probability and Conditional Probability
I came across this post of yours.
https://www.bionicturtle.com/forum/threads/p2-t6-307-hazard-rate-malz-section-7-2.6932/#post-42375
AND
What I do not understand is the difference between...
Here is a recent question I wrote to test Bayes Theorem (which has been reintroduced into the FRM)
1. Tree Approach
I have typically used a (binomial) tree to visualize this sort of problem. You start the tree with the unconditional (aka, marginal) probabilities which are the probabilities...
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