Japanese Journal of Statistics and Data Science

metrics 2024

Cultivating Knowledge at the Intersection of Data and Theory

Introduction

Japanese Journal of Statistics and Data Science, published by SPRINGERNATURE, is a leading academic journal dedicated to the advancement of statistical methodologies and data science applications, with a focus on fostering innovative research and discourse within the field. Since its inception in 2018, the journal has sought to bridge theory and practice, embracing emerging trends and interdisciplinary approaches that contribute to the ever-evolving landscape of statistics, probability, and computational theory. Hailing from Germany, the journal holds an impressive Q3 ranking in both Computational Theory and Mathematics and Statistics and Probability, reflecting its commitment to high-quality, impactful research. With an accessible ISSN of 2520-8756 and E-ISSN 2520-8764, the journal invites a global audience of researchers, professionals, and students to explore its rich array of articles and findings, all aimed at furthering knowledge and application in the realm of data science.

Metrics 2024

SCIMAGO Journal Rank-
Journal Impact Factor1.10
Journal Impact Factor (5 years)1.00
H-Index-
Journal IF Without Self1.10
Eigen Factor0.00
Normal Eigen Factor0.12
Influence0.41
Immediacy Index0.30
Cited Half Life2.70
Citing Half Life14.00
JCI0.65
Total Documents-
WOS Total Citations176
SCIMAGO Total Citations-
SCIMAGO SELF Citations-
Scopus Journal Rank-
Cites / Document (2 Years)-
Cites / Document (3 Years)-
Cites / Document (4 Years)-

Metrics History

Rank 2024

IF (Web Of Science)

STATISTICS & PROBABILITY
Rank 85/168
Percentile 49.70
Quartile Q3

JCI (Web Of Science)

STATISTICS & PROBABILITY
Rank 58/168
Percentile 65.48
Quartile Q2

Quartile History

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