Learning Outcome Statements PDF Download
|1. Sampling Methods|
compare and contrast probability samples with non-probability samples and discuss applications of each to an investment problem;
explain sampling error;
compare and contrast simple random, stratified random, cluster, convenience, and judgmental sampling;
|2. The Central Limit Theorem|
explain the central limit theorem and its importance;
|3. Standard Error of the Sample Mean|
calculate and interpret the standard error of the sample mean;
|4. Point Estimates of the Population Mean|
identify and describe desirable properties of an estimator;
contrast a point estimate and a confidence interval estimate of a population parameter;
|5. Confidence Intervals for the Population Mean and Selection of Sample Size|
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 population variance and a large sample size;
|7. Data Snooping Bias, Sample Selection Bias, Look-Ahead Bias, and Time-Period Bias|
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.
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