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Journal ranking is widely used in academic circles in the evaluation ... reflecting the number of citations accrued by the paper that resides at the top quartile (the ...
The three quartiles, resulting in four data divisions, are as follows: The first quartile (Q 1) is defined as the 25th percentile where lowest 25% data is below this point. It is also known as the lower quartile. The second quartile (Q 2) is the median of a data set; thus 50% of the data lies below this point.
The SCImago Journal Rank (SJR) indicator is a measure of the prestige of scholarly journals that accounts for both the number of citations received by a journal and the prestige of the journals where the citations come from.
JIF quartile ranking: a rank based on the four quartiles within a given subject or topic category. [97] JIF percentile ranking: a percentile rank computed for a particular subject category. [98] A given journal may attain a different quartile or percentile in different categories.
This is the minimum value of the set, so the zeroth quartile in this example would be 3. 3 First quartile The rank of the first quartile is 10×(1/4) = 2.5, which rounds up to 3, meaning that 3 is the rank in the population (from least to greatest values) at which approximately 1/4 of the values are less than the value of the first quartile.
The quartiles were numbered Q1, Q2, Q3 and Q4, with participants in Q1 clocking the least amount of physical activity. Each quartile went up from there, with participants in Q4 clocking the most ...
In any given year, the CiteScore of a journal is the number of citations, received in that year and in previous three years, for documents published in the journal during the total period (four years), divided by the total number of published documents (articles, reviews, conference papers, book chapters, and data papers) in the journal during the same four-year period: [3]
The lower quartile corresponds with the 25th percentile and the upper quartile corresponds with the 75th percentile, so IQR = Q 3 − Q 1 [1]. The IQR is an example of a trimmed estimator , defined as the 25% trimmed range , which enhances the accuracy of dataset statistics by dropping lower contribution, outlying points. [ 5 ]