Research Topic · Peer-Reviewed

Statistical Analysis

Statistical analysis is the application of mathematical methods to collect, summarize, model, and interpret data, enabling researchers to quantify uncertainty, detect patterns, and draw inferences about populations from samples. It spans descriptive techniques, hypothesis testing, regression and correlation, multiva…

Curated from this journal's research 📚 12 peer-reviewed articles cited Cited 21× across the literature 🔖 ISSN 2768-0207 🗓 Reviewed June 2026

Overview

Statistical analysis is the application of mathematical methods to collect, summarize, model, and interpret data, enabling researchers to quantify uncertainty, detect patterns, and draw inferences about populations from samples. It spans descriptive techniques, hypothesis testing, regression and correlation, multivariate modeling, and structural approaches such as structural equation modeling, and underlies the design and interpretation of empirical studies across the biological, clinical, and applied sciences. Sound analysis depends on appropriate study design, valid measurement, suitable model selection, and correct handling of variability and confounding, so that conclusions about association, prediction, or treatment effect are defensible. Across research domains it serves diverse ends, from epidemiological description of disease incidence and quantification of risk factors to optimization of experimental conditions and evaluation of interventions. The peer-reviewed studies indexed under this topic apply statistical methods to educational outcomes, regional cancer incidence, fermentation and bioprocess optimization, microbiological risk factors, biomarker and proteomics data, anthropometric modeling, and multivariate analysis of socioeconomic and environmental determinants of health. Together they illustrate the breadth of statistical practice, in which the choice and rigor of analytical methods are central to generating reliable, interpretable evidence from quantitative data across scientific and applied fields.

Research published in this journal

12 peer-reviewed articles, ranked by relevance. Each links to its DOI.

How this research is being cited

The 12 articles above have been cited 21 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.

A sample of recent works citing this journal's research on Statistical Analysis, linking to each citing work.

Editorial oversight

Curated from peer-reviewed research published in Big Data Research (ISSN 2768-0207).

Journal editorial board
Professor Shangming Zhou · United Kingdom Professor Hong Lin · United States Dr. Rami H. Al-Rifai · United Arab Emirates

This page summarises published research for orientation; it is not medical or professional advice.