IAI CM1 study plan

Set up a formula sheet covering survival models, force of mortality, and life-table functions, and derive each entry once from first principles

Derive expected present values of whole-life and term assurances directly from the sum over k of v^(k+1) times the deferred probability of death

Compute complete and curtate expectation of life from a given life table and reconcile the two values

Build a 60-problem timed drill set on actuarial notation conversions and score it

Derive net premiums for whole-life, term, endowment, and pure endowment contracts and explain how each differs

Compute net premium reserves prospectively and retrospectively and verify both methods agree on one worked example

Derive annuity-due and annuity-immediate relationships and convert between them under the uniform distribution of deaths assumption

Solve 25 mixed calculation problems combining premiums, reserves, and annuity factors under time pressure

Derive Thiele's differential equation and apply it to a simple two-state model

Compute transition probabilities in a multi-state Markov model by matrix exponentiation or Kolmogorov forward equations

Fit a Kaplan-Meier survival curve to a small right-censored dataset by hand and compute the Greenwood variance

Compare the Nelson-Aalen estimator with Kaplan-Meier on the same dataset and articulate when each is preferred

Derive the maximum likelihood estimator for exponential and Weibull models under right censoring and verify the score equations

Construct asymptotic confidence intervals for a fitted survival model parameter and interpret the coverage

Apply the log-rank test to two small samples and state the null hypothesis precisely

Distinguish parametric, semi-parametric, and nonparametric approaches and select the appropriate one for three described scenarios

Derive the distribution of the sample mean and state the central limit theorem conditions precisely

Compute method-of-moments and maximum likelihood estimators for common distributions and compare their properties

Derive the Cramer-Rao lower bound and use it to assess estimator efficiency

Perform a hypothesis test for a mean and a proportion, computing p-values and stating conclusions in context

Derive the least-squares estimator in matrix form and interpret the coefficient of determination

Construct and interpret confidence and prediction intervals in a simple linear regression

Apply generalized linear model concepts to a binary outcome using a logit link and interpret the coefficients

Compute the mean and variance of a compound Poisson aggregate loss model and explain the effect of frequency and severity assumptions

Complete one full timed mock exam under exam conditions and record per-question time allocation

Categorize every error as conceptual, computational, or misread and rank the categories by frequency

Re-derive from scratch the three formulas most implicated in your errors and confirm the derivations against your formula sheet

Reattempt every missed question cold, without notes, at least 48 hours after the mock

Complete a second full timed mock exam and compare per-topic accuracy against the week 7 baseline

Drill only the five weakest topics identified in week 7 until accuracy on each exceeds 85 percent

Rehearse exam-day logistics, including calculator modes, formula sheet usage, and time checkpoints at the 25, 50, and 75 percent marks

Review the formula sheet once end to end and flag any entry you cannot re-derive on demand