Explain and perform calculations conce ...
Joint Discrete Probability Distributions We are often interested in experiments that involve the... Read More
General Probability
1.a – Define set functions, Venn diagrams, sample space, and events. Define probability as a set function on a collection of events and state the basic axioms of probability.
1.b – Calculate probabilities using addition and multiplication rules.
1.c – Define independence and calculate probabilities of independent events.
1.d – Calculate probabilities of mutually exclusive events.
1.e – Define and calculate conditional probabilities.
1.f – Calculate probabilities using combinatorics, such as combinations and permutations.
1.g – State Bayes Theorem and the law of total probability and use them to calculate conditional probabilities.
Univariate Random Variables
2.a – Explain and apply the concepts of random variables, probability, probability density functions, and cumulative distribution functions
2.b – Calculate conditional probabilities
2.c – Explain and calculate expected value, mode, median, Percentile, and higher moments.
2.d – Explain and calculate variance, standard deviation, and coefficient of variation.
2.e – Apply the concepts of deductibles, coinsurance, benefit limits, and inflation to convert a given loss amount from a policyholder into the corresponding payment amount for an insurance company.
2.f – Calculate the expected value, variance, and standard deviation of both the loss random variable and the corresponding payment random variable upon the application of policy adjustments.
2.g – Determine the sum of independent random variables (Poisson and normal).
Multivariate Random Variables
3.a – Explain and perform calculations concerning joint probability functions and cumulative distribution functions for discrete random variables only.
3.b – Determine conditional and marginal probability functions for discrete random variables only.
3.c – Calculate moments for joint, conditional, and marginal random variables.
3.d – Calculate variance, standard deviation for conditional and marginal probability distributions.
3.e – Calculate joint moments, such as the covariance and the correlation coefficient.
3.f – Determine the distribution of order statistics from a set of independent random variables
3.g – Calculate probabilities and moments for linear combinations of independent random variables.
3.h – Calculate moments for linear combinations of independent random variables.
3.i – State and apply the Central Limit Theorem.
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Daniel Glyn
2021-03-24
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2021-03-18
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Nyka Smith
2021-02-18
Every concept is very well explained by Nilay Arun. kudos to you man!
Badr Moubile
2021-02-13
Very helpfull!
Agustin Olcese
2021-01-27
Excellent explantions, very clear!
Jaak Jay
2021-01-14
Awesome content, kudos to Prof.James Frojan
sindhushree reddy
2021-01-07
Crisp and short ppt of Frm chapters and great explanation with examples.