Technometrics

Aims & Scope

Technometrics is a Journal of Statistics for the Physical, Chemical, and Engineering Sciences, and is published Quarterly by the American Society for Quality and the American Statistical Association.

Since its inception in 1959, the mission of Technometrics has been to contribute to the development and use of statistical methods in the physical, chemical, and engineering sciences.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	2.5
2024	2.30

SJR (SCImago Journal Rank)

Year	Value
2024	1.408

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	96

Journal Rank

Year	Value
2024	2669

Journal Citation Indicator

Year	Value
2024	491

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Mathematics, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Ridge Regression: Biased Estimation for Nonorthogonal Problems

  Citation: 7114

  Authors: Arthur E., Robert W.

• Factorial Sampling Plans for Preliminary Computational Experiments

  Citation: 3567

  Authors: Max D.

• Multiple Comparisons Using Rank Sums

  Citation: 3161

  Authors: Olive Jean

• Computer Aided Design of Experiments

  Citation: 2846

  Authors: R. W., L. A.

• Some New Three Level Designs for the Study of Quantitative Variables

  Citation: 2729

  Authors: G. E. P., D. W.

• Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing

  Citation: 2693

  Authors: Diane

• Detection of Influential Observation in Linear Regression

  Citation: 2645

  Authors: R. Dennis

• Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter

  Citation: 2568

  Authors: Gene H., Michael, Grace

• A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code

  Citation: 2504

  Authors: M. D., R. J., W. J.

• Procedures for Detecting Outlying Observations in Samples

  Citation: 2446

  Authors: Frank E.

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