Sampling principles and strategies Flashcards
Simple Random Sample
A basic sampling method where each case in the population has an equal chance of being included, similar to selecting cases through a raffle.
Non-Response Rate
The percentage of people who do not respond in a survey or study, which can impact the reliability of the results.
Representative
A sample that accurately reflects the characteristics of the entire population, ensuring unbiased results.
Non-Response Bias
A type of bias that occurs when a high non-response rate skews results, making the sample unrepresentative of the population.
Convenience Sample
A sample where individuals who are easily accessible are more likely to be included, often leading to results that do not accurately represent the entire population. For example, surveying people in one specific location, like the Bronx, to represent all of New York City.
Prospective Study
An observational study that identifies individuals and collects data as events unfold over time. For example, The Nurses’ Health Study, which follows participants for years to assess influences on health outcomes.
Retrospective Study
An observational study that collects data after events have already occurred, such as by reviewing past events in medical records.
Stratified Sampling
A sampling method where the population is divided into groups called strata, and a random sample is taken within each stratum. For instance, dividing MLB players by team and randomly sampling players from each team.
Cluster Sample
A sampling method where the population is divided into groups called clusters, a fixed number of clusters are selected, and all observations within those clusters are included in the sample. For example, selecting entire neighborhoods and including everyone in those neighborhoods.
Multistage Sample
A sampling method similar to a cluster sample, but instead of including all observations in the selected clusters, a random sample is taken within each chosen cluster. For example, selecting neighborhoods (clusters) and randomly sampling individuals from each neighborhood.
Descriptive Statistics
A branch of statistics that involves summarizing and organizing data using measures such as central tendency, variability, and correlations.
Inferential Statistics
A branch of statistics that uses data from a sample to make general conclusions or predictions about a larger population, such as through polls or clinical trials.
Population
The entire set of people or cases targeted by a research study.
Sampling Bias
Occurs when a sample does not accurately reflect the characteristics of the population from which it was drawn, leading to distorted results.
Confounding Variable
A variable that is correlated with both the explanatory and response variables, potentially distorting the observed relationship between them.
