Affirm Journal of Statistics

Affirm Journal of Statistics is an international and peer-reviewed journal devoted to the dissemination of the full range of statistical thoughts at any technical level, The focus of the journal is on reporting significant and novel contributions in statistics, ranging across articles on statistical theory, methodology, applications, and computing. The editorial board of the journal invites authors to submit manuscripts relevant to statistical theories, methodologies, techniques, econometrics, and probability. At Affirm Journal of Statistics, we expect the researchers to abide rules of conducting ethical research. The accredited editorial board of the journal will have a close look at every single manuscript sent to the journal and are sensitive to issues such as ghostwriting, unethical research practices, and inscrutable research reports. Affirm Journal of Statistics abides Principles of Transparency and Best Practice in Scholarly Publishing suggested by The Committee on Publication Ethics (COPE), the Directory of Open Access Journals (DOAJ), the Open Access Scholarly Publishers Association (OASPA), and Scopus.

Scope and Focus

Applied Probability and Statistics / Models / Survival Analysis
Bayesian Analysis
Categorical Data Analysis
Computational and Graphical Statistics
Data Analysis
Data Mining Statistics
Econometric and Statistical Methods
Engineering Statistics
Environmental Statistics and Environmetrics
Experimental Design
General and Introductory Statistics
History of Statistics
Longitudinal Analysis
Medical Statistics and Epidemiology
Multivariate Analysis
Nonparametric Analysis
Pharmaceutical Statistics
Popular Interest Statistics
Probability and Mathematical Statistics
Quality, Productivity, and Reliability
Queuing Theory
Regression Analysis
Statistics and Probability
Statistical Genetics / Microarray Analysis
Statistical Software / Maple/ Mathematica / MATLAB / R/ S-PLUS / SAS / SPSS / Win BUGS
Statistics - Text, and Reference
Statistics for Finance, Business, and Economics
Statistics for Social Sciences
Time Series

Editor in chief


Abstracting and Indexing

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