Chapter 7: Estimation and Inference Flashcards
Parameter
A descriptive measure computed from or used to describe a population of data, conventionally represented by Greek letters.
Probability sampling
sampling plan that allows every member of the population to have an equal chance of being selected.
Non-probability sampling
A sampling plan dependent on factors other than probability considerations, such as a sampler’s judgment or the convenience to access data.
Stratified random sampling
A procedure that first divides a population into subpopulations (strata) based on classification criteria and then randomly draws samples from each stratum in sizes proportional to that of each stratum in the population.
Simple random sample
A subset of a larger population created in such a way that each element of the population has an equal probability of being selected to the subset.
Systematic sampling
A procedure of selecting every kth member until reaching a sample of the desired size. The sample that results from this procedure should be approximately random.
Sampling error
The difference between the observed value of a statistic and the estimate resulting from using subsets of the population.
Sampling distribution
The distribution of all distinct possible values that a statistic can assume when computed from samples of the same size randomly drawn from the same population.
Indexing
An investment strategy in which an investor constructs a portfolio to mirror the performance of a specified index.
Cluster sampling
A procedure that divides a population into subpopulation groups (clusters) representative of the population and then randomly draws certain clusters to form a sample.
Convenience sampling
A procedure of selecting an element from a population on the basis of whether or not it is accessible to a researcher or how easy it is for a researcher to access the element.
Judgmental sampling
A procedure of selectively handpicking elements from the population based on a researcher’s knowledge and professional judgment.
Central limit theorem
The theorem that states the sum (and the mean) of a set of independent, identically distributed random variables with finite variances is normally distributed, whatever distribution the random variables follow.
Resampling
A statistical method that repeatedly draws samples from the original observed data sample for the statistical inference of population parameters.
Jackknife
A resampling method that repeatedly draws samples by taking the original observed data sample and leaving out one observation at a time (without replacement) from the set.
