Exam P Syllabus – Learning Outcomes

Exam P Syllabus – Learning Outcomes

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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