WOW.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Stratified sampling - Wikipedia

    en.wikipedia.org/wiki/Stratified_sampling

    In statistics, stratified sampling is a method of sampling from a population which can be partitioned into subpopulations . Stratified sampling example. In statistical surveys, when subpopulations within an overall population vary, it could be advantageous to sample each subpopulation ( stratum) independently.

  3. Stratified randomization - Wikipedia

    en.wikipedia.org/wiki/Stratified_randomization

    Graphic breakdown of stratified random sampling. In statistics, stratified randomization is a method of sampling which first stratifies the whole study population into subgroups with same attributes or characteristics, known as strata, then followed by simple random sampling from the stratified groups, where each element within the same subgroup are selected unbiasedly during any stage of the ...

  4. Sampling (statistics) - Wikipedia

    en.wikipedia.org/wiki/Sampling_(statistics)

    Sampling (statistics) In statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population to estimate characteristics of the whole population. The subset is meant to reflect the whole population and statisticians ...

  5. Stratification (clinical trials) - Wikipedia

    en.wikipedia.org/wiki/Stratification_(clinical...

    Stratification (clinical trials) Stratification of clinical trials is the partitioning of subjects and results by a factor other than the treatment given. Stratification can be used to ensure equal allocation of subgroups of participants to each experimental condition. This may be done by gender, age, or other demographic factors.

  6. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    Different sampling designs and statistical adjustments may have substantially different impact on the bias and variance of estimators (such as the mean). [citation needed] An example of a design which can lead to estimation efficiency, compared to simple random sampling, is Stratified sampling. This efficiency is gained by leveraging ...

  7. Cluster sampling - Wikipedia

    en.wikipedia.org/wiki/Cluster_sampling

    In statistics, cluster sampling is a sampling plan used when mutually homogeneous yet internally heterogeneous groupings are evident in a statistical population. It is often used in marketing research. In this sampling plan, the total population is divided into these groups (known as clusters) and a simple random sample of the groups is ...

  8. Sample mean and covariance - Wikipedia

    en.wikipedia.org/wiki/Sample_mean_and_covariance

    The sample mean ( sample average) or empirical mean ( empirical average ), and the sample covariance or empirical covariance are statistics computed from a sample of data on one or more random variables . The sample mean is the average value (or mean value) of a sample of numbers taken from a larger population of numbers, where "population ...

  9. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    Sample size determination or estimation is the act of choosing the number of observations or replicates to include in a statistical sample. The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is usually determined ...