What type of variable is assumed to be a causal factor in relation to a dependent variable?

The independent variable is the assumed causal factor in relation to a dependent variable. In research, an independent variable is manipulated or controlled to observe the effect it has on the dependent variable. Essentially, researchers look to see how changes in the independent variable will lead to changes in the dependent variable.

For example, if a study aims to evaluate the effect of study hours (independent variable) on test scores (dependent variable), the amount of time spent studying is being manipulated to observe how it influences the scores achieved. This relationship is foundational in experimental design, as it allows researchers to establish causality between two variables.

In contrast, the dependent variable is what you measure in the experiment and what is affected during the experiment. The null hypothesis represents a statement that there is no effect or relationship, while external secondary data refers to previously gathered data that can be used for research analysis but is not a variable of interest in an experiment. Understanding the distinction between these concepts is crucial for effective research design and analysis.