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In publishing and library and information science, the term serial is applied to materials "in any medium issued under the same title in a succession of discrete parts, usually numbered (or dated) and appearing at regular or irregular intervals with no predetermined conclusion."
Statistical tests are used to test the fit between a hypothesis and the data. [1] [2] Choosing the right statistical test is not a trivial task. [1]The choice of the test depends on many properties of the research question.
Content usually takes the form of articles presenting original research, review articles, or book reviews.The purpose of an academic journal, according to Henry Oldenburg (the first editor of Philosophical Transactions of the Royal Society), is to give researchers a venue to "impart their knowledge to one another, and contribute what they can to the Grand design of improving natural knowledge ...
Informally, it is the similarity between observations of a random variable as a function of the time lag between them. The analysis of autocorrelation is a mathematical tool for finding repeating patterns, such as the presence of a periodic signal obscured by noise , or identifying the missing fundamental frequency in a signal implied by its ...
System suitability – A test run each time an analysis is performed to ensure the test method is acceptable and is performing as written. This type of check is often run in a QC Lab. Usually, system suitability is performed by analyzing a standard material (House standard or reference standard) before the unknowns are run in an analytical method.
Bibliometrics is the application of statistical methods to the study of bibliographic data, especially in scientific and library and information science contexts, and is closely associated with scientometrics (the analysis of scientific metrics and indicators) to the point that both fields largely overlap.
One way to make some time series stationary is to compute the differences between consecutive observations. This is known as differencing . Differencing can help stabilize the mean of a time series by removing changes in the level of a time series, and so eliminating trends.
Difference in differences (DID [1] or DD [2]) is a statistical technique used in econometrics and quantitative research in the social sciences that attempts to mimic an experimental research design using observational study data, by studying the differential effect of a treatment on a 'treatment group' versus a 'control group' in a natural experiment. [3]