In research, when an independent variable is manipulated, what is expected to be affected?

When the independent variable is manipulated in research, the expectation is that this manipulation will lead to a change in the dependent variable. The independent variable is what the researcher actively changes or controls in order to observe how it impacts other variables. The dependent variable is the outcome or response that is measured to assess the effect of the manipulation.

In a well-designed experiment, the researcher aims to isolate the effect of the independent variable on the dependent variable, which allows for clearer conclusions about cause and effect. The relationship hinges on the assumption that changes in the independent variable directly cause changes in the dependent variable. This is foundational to experimental research, as it seeks to establish causal relationships.

While confounding variables may also play a role in the outcomes, they are not the focus of the manipulation; rather, they need to be controlled for to ensure that any observed effects can be attributed directly to the independent variable. The options that suggest affecting only the independent variable or all variables equally do not align with the fundamental principles of how independent and dependent variables interact within research methodologies.