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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 ...
Given a sample of size , a jackknife estimator can be built by aggregating the parameter estimates from each subsample of size () obtained by omitting one observation. [ 1 ] The jackknife technique was developed by Maurice Quenouille (1924–1973) from 1949 and refined in 1956.
Cross-sectional data. In statistics and econometrics, cross-sectional data is a type of data collected by observing many subjects (such as individuals, firms, countries, or regions) at a single point or period of time. Analysis of cross-sectional data usually consists of comparing the differences among selected subjects, typically with no ...
In medical research, epidemiology, social science, and biology, a cross-sectional study (also known as a cross-sectional analysis, transverse study, prevalence study) is a type of observational study that analyzes data from a population, or a representative subset, at a specific point in time—that is, cross-sectional data.
Fisher's exact test is a statistical significance test used in the analysis of contingency tables. [ 1][ 2][ 3] Although in practice it is employed when sample sizes are small, it is valid for all sample sizes. It is named after its inventor, Ronald Fisher, and is one of a class of exact tests, so called because the significance of the ...
Size of bubbles represent the standard deviation of cross-validation accuracy (tenfold). [1] Diagram of k-fold cross-validation Cross-validation , [ 2 ] [ 3 ] [ 4 ] sometimes called rotation estimation [ 5 ] [ 6 ] [ 7 ] or out-of-sample testing , is any of various similar model validation techniques for assessing how the results of a ...
Repeated measures design. Repeated measures design is a research design that involves multiple measures of the same variable taken on the same or matched subjects either under different conditions or over two or more time periods. [ 1] For instance, repeated measurements are collected in a longitudinal study in which change over time is assessed.
Asymptotic theory (statistics) In statistics, asymptotic theory, or large sample theory, is a framework for assessing properties of estimators and statistical tests. Within this framework, it is often assumed that the sample size n may grow indefinitely; the properties of estimators and tests are then evaluated under the limit of n → ∞.