Variables (or factors)

A variable is an object, idea, or condition that can have multiple values or formats. Each variable has its own form among a possible set. Ex: variable reading medium > digital, text, etc.

In other words, it is a measurable characteristic that can take different values or modalities.

Examples: height, age, gender, income, country of birth, years of education, type of housing, etc.

In a research study, we will always seek to observe the effects of a variable whose values do not change (independent variable = IV) on another variable whose variations are measured (dependent variable = DV).

In a research study, we will formulate a hypothesis. The researcher will establish the hypothesis that the independent variable (whose values are fixed) will impact the dependent variable (the one being measured).

Variable 1 = what explains, what is fixed. It is the cause.
Variable 2 = what is explained, what is measured. It is the consequence.

There is a third type of variable, optional, in a research study. It is the controlled variable: it is a variable that must be taken into account and could impact the variation of the dependent variable.
Controlled Variable (or Confounding Variable) = what could impact the variations of the Dependent Variable (DV)

To facilitate understanding and the order of variables, it is common to say that the variable 2 (which is explained) depends on the variable 1 (which explains, which varies). Hence the name dependent or explained variable.

The dependent variable (DV) is the variable tested and measured by the experimenter in a scientific experiment.

To better understand:

The independent variable (IV) concerns what the experimenter identifies and controls. It is manipulated by the researcher through different modalities, but also through the different groups they set up.

An IV corresponds to characteristics identified as potential causes of the DV, such as:

• Individual characteristics (e.g., Gender, age, level of expertise, etc.).
• Physical or social environment (e.g., presence/absence of others, wall color, noisy vs. calm environment).
• The task (difficult vs. easy, familiar vs. unfamiliar).
• The nature of presented stimuli (e.g., ambiguous vs. non-ambiguous; subliminal vs. supra-liminal).

These characteristics are thus manipulated by the researcher to control or analyze their impact on participants' behavior, state, or mental processes.

An IV has at least 2 modalities or states (also called degrees, levels, or values) identified by the experimenter.

Modalities (or factors)*: The modalities of a variable are the different values that the independent variable can take.

For example, the modalities of the variable family situation are: Single, widowed, married, in a relationship, etc.

Important
To better distinguish the types of variables (independent and dependent), considering the cause/effect relationship can help.
If an independent variable is modified, then an impact should be found on the dependent variable. In other words, the evaluation of the dependent variable (measured) should not be the same depending on the modality of the independent variable. In the skiing example, Julie’s skiing performance should not be the same if she has not taken any ski lessons, if she has taken one, or if she has taken two.

The controlled variable is a "confounding variable" in the sense that it is likely to disrupt the dependent variable (which is measured).

This variable is fixed, just like the independent variables (voluntarily manipulated), but here, the researcher wants to control the effect of the controlled variable on the dependent variable. Controlled variables are not always identified, nor necessary.