About the Journal
The Journal of Data Science and Analytical Research is a peer-reviewed journal published by ISRN Journals with the aim of publishing high-quality papers in the field of data science, analytics, and evidence-based decision-making in various disciplines. It serves as an academic platform for researchers developing analytical methods, validating predictive models, and applying data science to solve problems in various domains, including business, healthcare, education, engineering operations, public policy, and social systems. The topics covered by this journal include statistical learning, predictive modeling, forecasting, classification, regression, time series analysis, experimental design, A/B testing, model evaluation, performance measurement, visualization, interpretation, explainability, data governance, and artificial intelligence. The journal prides itself on promoting transparency in the methods, models, validation techniques, and limitations used in the research, which helps readers to trust the findings and apply the work. Well-designed papers should include problem formulation, methodology, baselines, interpretation, implications, and should be realistic given the constraints of data quality, bias, uncertainty, and application limitations. Researchers interested in publishing their papers in a reputable journal for data science, analytics, machine learning, artificial intelligence, statistical modeling, or predictive analytics will find this journal’s topics relevant to modern analytical practices with proper academic standards.
Current Issue
Article Publication fee is $100.00
