Final answer:
Option (B), In research, the independent variable influences the dependent variable, but confounding variables can complicate establishing a cause-and-effect relationship. Random assignment is used to eliminate the impact of lurking variables, enabling researchers to isolate the effect of the independent variable.
Step-by-step explanation:
When conducting research, it is crucial to understand the relationship between the independent variable and the dependent variable. The independent variable is the variable that the researcher manipulates, while the dependent variable is the variable that is affected and measured in response to the independent variable.
However, identifying the direction of cause and effect can be problematic in non-experimental studies due to the presence of confounding variables, which are extraneous variables that could influence the outcome, making it challenging to determine the true effect of the independent variable on the dependent variable.
To mitigate the impact of confounding variables and establish a cause-and-effect relationship, random assignment of experimental units to treatment groups is utilized to ensure that other potential lurking variables are evenly distributed, thus isolating the effect of the independent variable.
A classic example of a problem in non-experimental research is when subjects are not assigned to treatment groups at random, resulting in differences between groups due to variables other than the independent variable. To attempt to prove causality, researchers often administer different treatments and measure the outcomes, with the goal of determining which treatment genuinely causes a change in the dependent variable.