# statistics

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## statistics

1. methods of collecting and analysing numerical data.
2. a group of data.

Businesspeople make considerable use of statistical methods such as collecting SAMPLES in order to make STATISTICAL INFERENCES in such areas as MARKETING RESEARCH and QUALITY CONTROL. They also use government economic data in monitoring changes in the business environment.

## statistics

1. a branch of mathematics that studies the theory and methods of collecting, tabulating and analysing numerical data.
2. a grouping of data. Economic analysis makes extensive use of economic data, which are subjected to statistical analysis in order to test ECONOMIC THEORIES. See HYPOTHESIS TESTING, ECONOMETRICS.
References in periodicals archive ?
I would certainly recommend, without any reservations, the use of this book in an undergraduate or graduate course on research and statistical methods in the social sciences.
The statistical methods that we compared were a) the EWAS approach; b) EWAS followed by a multiple regression step including the identified hits; c) ENET, a penalized regression method; d) sPLS regression, a supervised dimension reduction method; e) the Graphical Unit Evolutionary Stochastic Search (GUESS) algorithm, a computationally optimized Bayesian variable selection method (Bottolo et al.
KEY WORDS: Biostatistics, Statistical analysis, Study design, Statistical methods, Bibliometric analysis.
When the team members analyzed the Indian monsoon data using their statistical methods, they discovered that although the average total rainfall during the monsoon season has declined, the variability of rainfall during the peak monsoon months has increased.
The first article in the series, by Linnet and coworkers, reviews statistical methods used for the evaluation of single biomarkers (4).
As a result, the analysis must be completed by using different statistical methods that use circular variables, taking both direction and distance into account.
Sami was of the view that the workshop would help young researchers in developing a clear understanding of analyzing biological data, using correct statistical methods including interpretation of results and reporting in statistical language.
This text is intended for molecular biologists who perform quantitative analyses and for statisticians who work with molecular biologists and other biomedical researchers and aims to balance the needs of these two audiences by progressively introducing basic to intermediate statistical methods and demonstrating their application to the various biological data generated from the field of molecular biology and the types of questions of interest to molecular biologists.
New statistical methods could offer a more accurate assessment than traditional methods, Benjamin Baumer reported August 5.
The application includes a range of basic statistical methods and advanced multivariate statistical methods, such as descriptive statistics, t-test, f-test, nonparametric test, factor analysis, principal component analysis, cluster analysis, discrimination analysis, and correspondence analysis.

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