Sample Moments: A Review
1. Context
In this video from FRM Part 1 curriculum, we do a quick review of the reading on Sample Moments (Book 2, Quantitative Analysis, Chapter 5). The learning objectives covered are listed below:
- Estimate the mean, variance and standard deviation using sample data.
- Explain the difference between a population moment and a sample moment.
- Distinguish between an estimator and an estimate.
- Describe the bias of an estimator and explain what the bias measures.
- Explain what is meant by the statement that the mean estimator is BLUE.
- Describe the consistency of an estimator and explain the usefulness of this concept.
- Explain how the Law of Large Numbers (LLN) and Central Limit Theorem (CLT) apply to the sample mean.
- Estimate and interpret the skewness and kurtosis of a random variable.
- Use sample data to estimate quantiles, including the median.
- Estimate the mean of two variables and apply the CLT.
- Estimate the covariance and correlation between two random variables.
- Explain how coskewness and cokurtosis are related to skewness and kurtosis.
This video is an addendum to the preparation course for FRM Exam Part 1 (https://www.finRGB.com/courses/frm-part-1-online-course). The details of the reading in which this topic appears are given below:
Area | Quantitative Analysis |
Reading | Sample Moments |
Reference | Chapter 5. Sample Moments, Official GARP Books (QA Section, 2021). |