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Learning Outcome Statements PDF Download
a. define simple random sampling and a sampling distribution;
b. explain sampling error;
c. distinguish between simple random and stratified random sampling;
|2. Time-Series and Cross-Sectional Data|
d. distinguish between time-series and cross-sectional data;
|3. The Central Limit Theorem|
e. explain the central limit theorem and its importance;
|4. Standard Error of the Sample Mean|
f. calculate and interpret the standard error of the sample mean;
g. identify and describe desirable properties of an estimator;
h. distinguish between a point estimate and a confidence interval estimate of a population parameter;
|6. Confidence Intervals for the Population Mean|
i. describe properties of Student's t-distribution and calculate and interpret its degrees of freedom;
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;
|7. Common Biases in Sampling Methods|
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.