Sampling and Estimation

CFA level I / Quantitative Methods: Application / Sampling and Estimation

Learning Outcome Statements

1. Simple random sampling and sampling distribution
a. define simple random sampling and a sampling distribution;

2. Sampling error
b. explain sampling error;

3. Simple random and stratified random sampling
c. distinguish between simple random and stratified random sampling;

4. Time-series and cross-sectional data
d. distinguish between time-series and cross-sectional data;;

5. Central limit theorem
e. explain the central limit theorem and its importance;

6. Standard error of the sample mean
f. calculate and interpret the standard error of the sample mean;

7. Desirable properties of an estimator
g. identify and describe desirable properties of an estimator;

8. Point estimate and confidence interval estimate of a population parameter
h. distinguish between a point estimate and a confidence interval estimate of a population parameter;

9. Student's t-distribution and its degrees of freedom
i. describe properties of Student’s t-distribution and calculate and interpret its degrees of freedom;

10. Confidence interval for a population mean with a known and an unknown variance
j. calculate and interpret a confidence interval for a population mean, given a normal distribution with 1) a known population variance, 2) an unknown population variance, or 3) an unknown variance and a large sample size;

11. Data-mining bias, sample selection bias, survivorship bias, look-ahead bias, and time-period bias
k. describe the issues regarding selection of the appropriate sample size, data-mining bias, sample selection bias, survivorship bias, look-ahead bias, and time-period bias.

Sampling and Estimation: Chapter Test
12 Questions, 18 Minutes