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  2. Stratified sampling - Wikipedia

    en.wikipedia.org/wiki/Stratified_sampling

    Proportionate allocation uses a sampling fraction in each of the strata that are proportional to that of the total population. For instance, if the population consists of n total individuals, m of which are male and f female (and where m + f = n), then the relative size of the two samples (x 1 = m/n males, x 2 = f/n females) should reflect this proportion.

  3. Sampling (statistics) - Wikipedia

    en.wikipedia.org/wiki/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 attempt to collect ...

  4. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    Sample sizes may be evaluated by the quality of the resulting estimates, as follows. It is usually determined on the basis of the cost, time or convenience of data collection and the need for sufficient statistical power. For example, if a proportion is being estimated, one may wish to have the 95% confidence interval be less than 0.06 units wide.

  5. 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 ...

  6. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data analysis focuses on extracting insights and drawing conclusions from structured data, while data science involves a more comprehensive approach that combines statistical analysis, computational methods, and machine learning to extract insights, build predictive models, and drive data-driven decision-making. Both fields use data to ...

  7. Statistics - Wikipedia

    en.wikipedia.org/wiki/Statistics

    Astrostatistics (statistical evaluation of astronomical data) Biostatistics; Chemometrics (for analysis of data from chemistry) Data mining (applying statistics and pattern recognition to discover knowledge from data) Data science (see also: Data science#Relationship to statistics) Demography (statistical study of populations)

  8. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data science process flowchart from Doing Data Science, by Schutt & O'Neil (2013) Analysis refers to dividing a whole into its separate components for individual examination. [ 10 ] Data analysis is a process for obtaining raw data , and subsequently converting it into information useful for decision-making by users. [ 1 ]

  9. Statistical theory - Wikipedia

    en.wikipedia.org/wiki/Statistical_theory

    The theory of statistics provides a basis for the whole range of techniques, in both study design and data analysis, that are used within applications of statistics. [1] [2] The theory covers approaches to statistical-decision problems and to statistical inference, and the actions and deductions that satisfy the basic principles stated for these different approaches.