alexa Multivariate-data-analysis-High-Impact-Factor-Journals | Journal Of Biometrics And Biostatistics

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Multivariate-data-analysis-High-Impact-Factor-Journals

Multivariate Data Analysis refers to any statistical technique used to analyze data that arises from more than one variable. This essentially models reality where each situation, product, or decision involves more than a single variable. The information age has resulted in masses of data in every field. Despite the quantum of data available, the ability to obtain a clear picture of what is going on and make intelligent decisions is a challenge. When available information is stored in database tables containing rows and columns, Multivariate Analysis can be used to process the information in a meaningful fashion. High-impact journals are those considered to be highly influential in their respective fields. The impact factor of journal provides quantitative assessment tool for grading, evaluating, sorting and comparing journals of similar kind. It reflects the average number of citations to recent articles published in science and social science journals in a particular year or period, and is frequently used as a proxy for the relative importance of a journal within its field. It is first devised by Eugene Garfield, the founder of the Institute for Scientific Information. The impact factor of a journal is evaluated by dividing the number of current year citations to the source items published in that journal during the previous two years.
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Last date updated on September, 2014

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