Variables

- Overview

Variables are characteristics that can be measured and can take on different values. They can be found in a research question or hypothesis. 

In mathematics, a variable (from Latin variabilis, "changeable") is a symbol that represents a mathematical object. A variable may represent a number, a vector, a matrix, a function, the argument of a function, a set, or an element of a set. 

Variables are categorized in a variety of ways, including: 

• Independent variables: A variable that stands alone and is not changed by other variables. For example, a person's age.
• Dependent variables: A variable that changes as a result of the independent variable. Also called response variables. For example, how much a dog eats.
• Continuous variables: A variable that can take any value between two numbers. For example, the height of a group of basketball players.
• Discrete variables: A variable that takes on distinct, countable values.
• Confounding variables: A factor other than the one being studied that is associated with both the dependent and independent variables. A confounding variable may distort or mask the effects of another variable.

Other types of variables include: quantitative variables, qualitative variables, intervening variables, moderating variables, extraneous variables.

Please refer to Wikipedia: Variable for more details.

- Identifying Variables

Identifying variables before conducting an experiment is important for a few reasons:

• Define and measure factors: Identifying variables helps researchers clearly define and measure the factors being studied. This improves the reliability and validity of the research findings.
• Select appropriate methods: Understanding variables helps researchers select appropriate research methods and statistical analyses.
• Know what to experiment on: Identifying variables helps researchers know which items to experiment on and which to measure and get results from.
• Identify confounding variables: Identifying confounding variables helps ensure that the relationship being observed between independent and dependent variables is real, and that the results of a study are valid.
• Control variables: Control variables help ensure that the experiment results are fair, unskewed, and not caused by your experimental manipulation. For example, having the same glassware for all experiments is a controlled variable.
• Take variables into account: When scientists are aware of all variables, they can take them into account as they try to make sense of their results.