"Sampling is the selection of a subset or a statistical sample of individuals from within a statistical population to estimate characteristics of the whole population."
Methods used to select a representative sample from a population for statistical analysis, such as simple random sampling and stratified sampling.
Simple random sampling: A method where each member of the population has an equal chance of being selected for the sample.
Stratified random sampling: A method where the population is divided into strata (subgroups) and a sample is taken from each stratum.
Cluster sampling: A method where the population is divided into clusters (groups) and a sample is taken from each cluster.
Systematic sampling: A method where the population is ordered and every nth member is selected to be part of the sample.
Convenience sampling: A non-probability method where individuals are selected based on their availability and willingness to participate.
Snowball sampling: A non-probability method where participants are asked to recruit others to participate in the study.
Sampling frame: A list of members of the population from which the sample is selected.
Sampling error: The difference between the sample statistic and the population parameter.
Sample size: The number of individuals selected for the sample.
Sampling distribution: The distribution of all possible sample statistics from a given population.
Confidence interval: An interval estimate of the population parameter based on the sample statistic.
Margin of error: The range within which the true population parameter is likely to fall based on the sample statistic.
Sampling bias: A type of error that occurs when certain members of the population are more likely to be selected for the sample than others.
Non-response bias: A type of bias that occurs when members of the population selected for the sample do not participate in the study.
Response bias: A type of bias that occurs when participants in the study provide inaccurate or misleading information.
Sampling frame error: A type of error that occurs when the sampling frame does not accurately represent the population.
Randomization: A process used to ensure that each member of the population has an equal chance of being selected for the sample.
Stratification: The process of dividing the population into subgroups based on certain characteristics.
Weighting: A technique used to adjust the sample to better reflect the population.
Oversampling: A technique used to increase the representation of a particular subgroup in the sample.
Simple random sampling: Each member of the population has an equal chance of being selected.
Stratified sampling: The population is first divided into homogeneous groups or strata, and then a random sample is taken from each stratum.
Systematic sampling: Every nth member of the population is selected after a random starting point.
Cluster sampling: The population is divided into clusters or groups, and a random sample of clusters is taken.
Convenience sampling: The sample is selected based on availability and accessibility.
Judgmental sampling: The sample is selected based on the judgment of the researcher or expert.
Quota sampling: The sample is selected based on quotas set for different demographic groups.
Snowball sampling: Participants are selected based on referrals from existing participants.
Multi-stage sampling: A combination of two or more of the above sampling techniques is used.
Purposive sampling: A sample is selected based on specific criteria, such as age, gender, or occupation.
Voluntary response sampling: Participants self-select to be part of the sample, leading to potential bias.
Oversampling: A deliberate attempt is made to oversample a particular group for more accurate representation.
Replacement sampling: Members of the population can be selected multiple times during the sampling process.
Random-digit dialing: A technique used in phone surveys to randomly select phone numbers to call.
Probability proportional to size sampling: Larger subgroups of the population have a higher likelihood of being selected.
Sequential sampling: Sampling is carried out in a sequence until a sufficient sample size is achieved.
Time-lag sampling: Sampling is carried out at different points in time to capture changes in the population.
Referral sampling: Participants are recruited through referrals from professionals or experts in the field.
Quasi-random sampling: A sampling technique that is not completely random but incorporates some randomness.
Delayed sampling: Sampling is delayed to account for temporary changes in the population.
"Statisticians attempt to collect samples that are representative of the population."
"Sampling has lower costs and faster data collection compared to recording data from the entire population."
"It can provide insights in cases where it is infeasible to measure an entire population."
"Each observation measures one or more properties (such as weight, location, colour, or mass) of independent objects or individuals."
"In survey sampling, weights can be applied to the data to adjust for the sample design, particularly in stratified sampling."
"In business and medical research, sampling is widely used for gathering information about a population."
"Acceptance sampling is used to determine if a production lot of material meets the governing specifications."
"In statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample of individuals from within a statistical population."
"The selection of a subset or a statistical sample of individuals from within a statistical population to estimate characteristics of the whole population."
"Sampling in statistics, quality assurance, and survey methodology is the selection of a subset or a statistical sample of individuals."
"Statisticians attempt to collect samples that are representative of the population."
"Sampling has lower costs and faster data collection compared to recording data from the entire population."
"Weights can be applied to the data to adjust for the sample design, particularly in stratified sampling."
"Business and medical research widely use sampling for gathering information about a population."
"Acceptance sampling is used to determine if a production lot of material meets the governing specifications."
"Results from probability theory and statistical theory are employed to guide the practice."
"Sampling is the selection of a subset or a statistical sample of individuals from within a statistical population."
"Results from probability theory and statistical theory are employed to guide the practice."
"Weights can be applied to the data to adjust for the sample design, particularly in stratified sampling."