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SAMPLING- statistical process of selecting a subset (Sample) of a…
SAMPLING- statistical process of selecting a subset (Sample) of a population of interest for purposes of making observations and statistical inferences about that population.
POPULATION- The group you want to generalize to. all people or items (unit of analysis) w/ the characteristics that one wishes to study.
STATISTIC OF SAMPLING
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NORAML DISTRIBUTION-Large # of responses in a sample, this frequency distribution tends to resemble a bell-shaped curve, which can be used to estimate overall characteristics of the entire sample
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POPULATION PARAMETERS- Since the entire population can never be sampled,
SAMPLING ERROR- Statistics may differ from population parameters if the sample is not perfectly representative of the population.
SAMPLING DISTRIBUTION- is a probability distribution of a statistic obtained through a large number of samples drawn from a specific population. The sampling distribution of a given population is the distribution of frequencies of a range of different outcomes that could possibly occur for a statistic of a population.
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CONFIDENCE INTERVAL- The estimated probability that a population parameter lies within a specific interval of sample statistic values.
PROBABILITY SAMPLING- every unit in the population has a chance (non-zero Probability) of being selected in the sample, and this chance can be accurately determined.
SYSTEMATIC SAMPLING-The sampling frame is ordered according to some criteria and elements are selected at regular intervals through that ordered list
SIMPLE RANDOM SAMPLING-All possible subsets of a population(more accurately, of a sampling frame) are given an equal probability of being selected.
STRATIFIED SAMPLING- The sampling frame is divided into homogeneous and non-overlapping subgroups (strata) and a sample random sample is drawn within each subgroup.
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MATCHED-PAIRS SAMPLING- Are paired up so that the participants share every characteristic except for the one under investigation. A common use for matched pairs is to assign one individual to a treatment group and another to a control group.
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SAMPLING FRAME- A list from where you can draw your sample. the accessible section of the target population from where a sample can be drawn.
NON-PROBABILITY SAMPLING-Technique in which some units of the population have zero chance of selection or where the probability of selection cannot be accurately determined.
CONVENIENCE SAMPLING- accidental or opportunity sampling-sample is drawn from that part of the population that is close to hand, readily available, or convenient.
QUOTA SAMPLING- To take a very tailored sample that’s in proportion to some characteristic or trait of a population
PROPORTIONAL QUOTA SAMPLING- The proportion of respondents in each subgroup should matchthat of the population.
NON-PROPORTIONAL QUOTA SAMPLING- Is less restrictive in that you don't have to achieve a proportional representation, but perhaps meet a minimum size in each subgroup.
EXPERT SAMPLING- Respondents are chosen in a non-random manner based on their expertise on the phenomenon being studied.
SNOWBALL SAMPLING-Start by identifying a few respondents that match the criteria for inclusion in your study, and then ask them to recommend others they know who also meet your selection criteria.