FinAcademy › Risk Track I › Inference

Module R3 · QTA 5–6

From sample to conclusion

Estimators and what makes them good, the law of large numbers and the central limit theorem, then the hypothesis-testing recipe with p-values, confidence intervals and the two error types.

4 lessons · 11 interactive figures · 28 exercises

1. 1Estimators, the law of large numbers and the CLT
   A sample mean is itself a random variable. The CLT says what its distribution is, and the standard error says how wide.7 exercises
2. 2Sample skewness, kurtosis, quantiles and covariance
   The four moments again, now estimated from data, with the standard errors that make "the kurtosis is 5" mean something.7 exercises
3. 3The hypothesis-testing recipe
   Null, statistic, distribution, decision. Every test in the exam is the same four steps with a different statistic.7 exercises
4. 4Tests on means, testing alpha, and the multiple-testing trap
   A t-test on a fund's alpha is the exam's favourite. Run twenty of them and one will be "significant" by luck.7 exercises