A characteristic on which the elements of a population or sample differ from each other is called a...

A characteristic on which the elements of a population or sample differ from each other is called a variable. In statistical terms, a variable reflects the changes or differences among the elements being studied. For example, in a study on height, the variable would be height itself, as individuals in the sample can vary in that characteristic.

Variables can be classified into different types, such as qualitative (categorical) and quantitative (numerical), and they play a crucial role in data analysis because they help to identify patterns, relationships, and differences among data points. This concept is foundational in both descriptive and inferential statistics, facilitating the comparison between different groups or conditions and serving as a basis for hypotheses testing and predictive modeling.

Understanding the concept of variables is essential for anyone involved in data analysis, as it allows researchers to categorize and quantify the differences that drive insights and conclusions from their studies.