Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Inequalities

Inequalities

Inequalities express mathematical relationships where two values are not equal and are compared using symbols such as <, >, ≤, or ≥. These expressions define a range of possible solutions rather than a single value. Interval notation provides a concise way to express these solution sets, especially when the variable spans a continuous range. An open interval, written as (a, b), excludes the endpoints, while a closed interval [a, b] includes them. There are also half-open intervals, such...

Measures of Central Tendency

Measures of Central Tendency

The "center" of a data set is also a way of describing location. The two most widely used measures of the "center" of the data are the mean (average) and the median. The words "mean" and "average" are often used interchangeably. The substitution of one word for the other is common practice. The technical term is "arithmetic mean" and "average" is technically a center location. However, in practice among non-statisticians, "average" is commonly accepted for "arithmetic mean."

Skewness

Skewness

The measures of central tendency calculated from a data set may not reveal much about its intrinsic distribution. If a plot is made of the data set’s values, the mean and the median may not only differ, but also the plot may have more values on one side of the central tendencies. Such a data set is said to be skewed towards that side.
The longer the tail of the plot on one side, the more skewed it is. The skewness of a data set’s values suggests that the measures of central tendency are...

Introduction to Nonlinear Inequalities

Introduction to Nonlinear Inequalities

Linear and nonlinear inequalities are fundamental for analyzing variable relationships and identifying ranges satisfying specific conditions. A linear inequality involves variables raised only to the first power, resulting in a straight-line graph. This line partitions the coordinate plane into two distinct regions: one that satisfies the inequality and one that does not. Each region represents a set of solutions where the linear relationship holds true under the specified constraint.Nonlinear...

Solving Inequalities Graphically

Solving Inequalities Graphically

Solving inequalities graphically involves using a visual approach to determine where a mathematical expression meets a specific condition, such as being greater than or less than another value. By examining the position of a graph relative to the x-axis or another graph, it becomes possible to identify the range of x-values that satisfy the inequality. This method provides an intuitive understanding of solution intervals by showing where the inequality holds true.Graphical solutions to...

Application of Nonlinear Inequalities

Application of Nonlinear Inequalities

A nonlinear inequality describes a comparison involving an expression that curves or behaves more complexly than a straight line. These inequalities often appear in forms that include squares, products, or variables in the denominator.To solve such an inequality, one starts by rewriting it so that zero appears on one side. For example, the inequality: can be factored as: This form makes it easier to identify the values that cause the expression to equal zero. In this case, the key values are 3...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Racial Health Equity Plans in the 30 Largest US Cities.

Journal of racial and ethnic health disparities·2023

Same author

Developing and Implementing Racial Health Equity Plans in Four Large US Cities: A Qualitative Study.

Journal of public health management and practice : JPHMP·2023

Same author

Life Expectancy Gaps Among Black and White Persons and Contributing Causes of Death in 3 Large US Cities, 2018-2019.

JAMA network open·2023

Same author

A Call for Antiracist Action.

The New England journal of medicine·2022

Same author

Comparison of All-Cause Mortality Rates and Inequities Between Black and White Populations Across the 30 Most Populous US Cities.

JAMA network open·2021

Same author

Homicide Mortality Inequities in the 30 Biggest Cities in the U.S.

American journal of preventive medicine·2020

Search research articles

Related Experiment Video

Updated: Jul 11, 2026

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

Income inequality measures.

Fernando G De Maio¹

¹Simon Fraser University, Burnaby, British Columbia, Canada. fdemaio@sfu.ca

Journal of Epidemiology and Community Health

|September 18, 2007

Summary

The Gini coefficient is common for measuring income inequality, but alternative methods like the generalized entropy and Atkinson indices offer a more detailed understanding of income distribution across different economic levels.

Area of Science:

Public Health
Economics
Sociology

Background:

The Gini coefficient is widely used in public health research to measure income inequality.
Existing methods may not fully capture the nuances of income distribution.

Purpose of the Study:

To introduce alternative income inequality measures beyond the Gini coefficient.
To provide a conceptual understanding of various income distribution assessment tools.

Main Methods:

Conceptual review of income inequality metrics.
Explanation of the generalized entropy index.
Explanation of the Atkinson index.

Main Results:

Alternative measures like generalized entropy and Atkinson indices allow for nuanced analysis of income inequality.

Related Experiment Videos

Last Updated: Jul 11, 2026

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

These methods enable examination of inequality at different points of the income spectrum.

Qualitatively different inequalities can be assessed more meaningfully.

Conclusions:

Researchers can gain a more sophisticated understanding of income distribution by employing diverse inequality measures.
Alternative indices provide a richer quantitative assessment of economic disparities.