Research Topic · Peer-Reviewed

Normal Distribution

Normal Distribution is a special type of statistical distribution which is bell shaped and symmetric and is defined by the mean and the standard deviation. It is an important concept in probability theory and is used extensively in the sciences and in many business and economic applications. The Normal Distribution …

Curated from this journal's research 📚 11 peer-reviewed articles cited Cited 114× across the literature 🔖 ISSN 2643-2811 🗓 Reviewed June 2026

Overview

Normal Distribution is a special type of statistical distribution which is bell shaped and symmetric and is defined by the mean and the standard deviation. It is an important concept in probability theory and is used extensively in the sciences and in many business and economic applications. The Normal Distribution is also known as a Gaussian Distribution or bell curve. It has many uses in the fields of finance, economics and statistics and is used to model the probability of a certain event or variable like stock market returns, grades or test scores, or to represent the likelihood of certain outcomes in a study. The Normal Distribution is also used in machine learning and deep learning to model probability distributions and to build predictive models.

Research published in this journal

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

How this research is being cited

The 11 articles above have been cited 114 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 Normal Distribution, linking to each citing work.

Editorial oversight

Curated from peer-reviewed research published in Model Based Research (ISSN 2643-2811).

Journal editorial board
Yoshiaki Kikuchi · Japan Yung-Yao Chen · Taiwan Yang Chen · United States

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