Probability Concepts (2023 CFA® Level I Exam - Quantitative Methods - Module 3)
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- Опубликовано: 27 июл 2024
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Topic 1 - Quantitative Methods
Reading 3 - Probability Concepts
0:00 Introduction
2:21 LOS : Define a random variable, an outcome, and an event.
3:32 LOS : Identify the two defining properties of probability, including mutually exclusive and exhaustive events, and compare and contrast empirical, subjective, and a priori probabilities
8:45 LOS : Describe the probability of an event in terms of odds for and against the event
LOS : Calculate and interpret conditional probabilities
9:48 LOS : Demonstrate the application of the multiplication and addition rules for probability
15:55 LOS : Compare and contrast dependent and independent events
16:43 LOS : Calculate and interpret an unconditional probability using the total probability rule
19:16 LOS : Calculate and interpret the expected value, variance, and standard deviation of random variables
24:52 LOS : Explain the use of conditional expectation in investment applications
27:00 LOS : Interpret a probability tree and demonstrate its application to investment problems
31:16 LOS : Calculate and interpret the expected value, variance, standard deviation, covariances, and correlations of portfolio returns
41:11 LOS : Calculate and interpret the covariances of portfolio returns using the joint probability function
51:34 LOS : Calculate and interpret an updated probability using Bayes’ formula
55:41 LOS : Identify the most appropriate method to solve a particular counting problem and analyze counting problems using factorial, combination, and permutation concepts
i don't know what i'd do without these videos! best free cfa l1 content there is!
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I use Schweser materials for my initial studies, but these are SOOO much easier to comprehend then Schweser's review courses!
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Hello,
Thank you so much for the videos they are very helpful.
I would however add two comments:
firstly the question at 54:04 is not clear at all. " The probability of a train arriving late in NY, LV, WDC are ..." these should be understood as joint probabilities not conditional probabilities. I think the question needs to be reformulated for clarity.
Next I have an issue with 58:50 where one formula is written and another is used. the denominators should all have factorials. This is obviously a typo but could be misleading.
Again sheer excellence from you, Professor!
Its a great addition to the excercise book from the institute, because you explain the concepts in a unique way with good examples and are very pleasant to listen to.
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Thank you for the well-articulated and simplified explanations.
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From Brazil, learning and watching these amazing class
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Thank you Professor!
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Great video! Thanks for making these. Super helpful
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Great sessions, watching from South Africa.
Thank you for this great video.
You have a lot of free learning resources here, so you should create a link for people to donate for the continuation of your good work.
Thank you very much!
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Great Lesson, Thanks a lot
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At 39:03 the probabilities (that must sum to 1) if they aren't known, how do I calculate it for the scenarios(in this case the sales being 50,40,30)?
Where can I find the presentations to download them?
Would appreciate your response, Professor.
And thanks for the effort and the great explanation.
for the question on screen at 55:46 , is 50C3 + 50C4 the answer
Dear Mr. I would need help to understand following related to multiplication/addition rules:
1. if we presume, that two events occured together, how will we decide, if they are dependent or independent? if we seek to calculate the probability of the club winning given that rainy weather, how can we conclud that the rain is conditional or unconditional? If we presume that club won when it was raining 30% time and 70% not (based on what was the case in some period) and we want to know the probability of winning the club if it rains, how we conclude that it is conditional or unconditional probability? it can have nothing to do with weather so each of the results says nothing on the relationship of the two. Could you please share your thoughts?
2. from the examples on addition and multiplication rule you mentioned that multiplication rules concerns independent and dependent situations but on addition rule you mentioned that it concerns mutually exclusive and non-mutually exclusive events. I don't understand. Is it the rule that each independent is non-mutually exlusive and each dependent is mutually exclusive? what is the reasoning behind? if we take an example of the balls in the hat you mentioned, I presume the probability would be calculated differently if we say that the balls are given back to the hat once drawn i.e. what would be the calculation? P(AB) = P(A)P(B) = 16/30x16/30?
3. if we take the balls example from the point 2. above, and we would look for the probability of (A or B), what do instruction can look like and how it can not look like?
In minute 54 problem, im not getting the logic behind it, it only half the trains go to NY, and from those trains only 40% are late, how can the poasibility to pick a random train be late AND in NY be more the 50%?
great job
You're welcome!
Please elaborate the concept of quantile
Sir there's a confusion
For conditional probability
We apply multiplication rule
And for unconditional probability
We apply addition rule
Hello Professor, It looks like the answer for the covariance between Stock A and Stock B is not right. I am getting -4.788x10^-4
Great Lessons but for conditional probability does order matter
Great lecture, but excuse me...is not it that covariance only gives direction and correlation tends to show the strength and also direction? :)
hello, at 44:25, it is unclear how you arrived at the product of deviations for each stock
（2.3-5.72）*（6.5-4.4）=-7.182
where do we get the ppt from??
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