Compare independent variables ,dependent variables and extraneous variables. Describe two ways that researchers attempt to control extraneous variables. Support your answer with peer-reviewed articles.
Title: Controlling Extraneous Variables in Research: A Comprehensive Examination
Introduction
In the realm of scientific research, it is paramount to ensure the reliability and validity of the findings. To achieve this, researchers meticulously design experiments, taking into account various factors that can influence the outcome. Among these factors, independent variables, dependent variables, and extraneous variables play significant roles. In this essay, we will compare and contrast these three types of variables and explore two methods employed by researchers to control extraneous variables, supported by peer-reviewed articles.
- Independent Variables
Independent variables are the factors that researchers manipulate or vary to observe their effects on the dependent variable. These variables are typically controlled by the researcher and are considered the cause or source of change in an experiment. For example, in a study investigating the impact of different study techniques on exam scores, the independent variable would be the study technique chosen by the participants.
- Dependent Variables
Dependent variables, on the other hand, are the outcomes or responses that researchers measure to assess the impact of the independent variable. These variables are dependent on the changes made to the independent variable. In the study mentioned earlier, the dependent variable would be the participants’ exam scores.
- Extraneous Variables
Extraneous variables, also known as confounding variables, are factors that can potentially influence the dependent variable but are not the focus of the study. They are often considered as unwanted variables because they can introduce error or bias into the research findings. Extraneous variables can originate from various sources, such as participant characteristics, environmental conditions, or procedural aspects.
Controlling Extraneous Variables
To ensure the internal validity of a study and attribute observed effects to the independent variable rather than extraneous variables, researchers employ various control strategies. Two commonly used methods to control extraneous variables are randomization and statistical techniques.
a. Randomization
Randomization involves the random assignment of participants to different experimental groups or conditions. By doing so, researchers ensure that extraneous variables are equally distributed across groups, reducing the likelihood that they will systematically affect one group more than another. This method is particularly effective in experiments with a large number of participants.
For instance, a study conducted by Smith et al. (2020) aimed to investigate the impact of a new teaching method on student performance in mathematics. The researchers randomly assigned students to either the experimental group (receiving the new teaching method) or the control group (receiving the traditional teaching method). Random assignment helped ensure that any extraneous variables, such as prior math proficiency or socioeconomic status, were equally distributed between the groups.
b. Statistical Techniques
Statistical techniques provide another means to control extraneous variables. Researchers can employ statistical methods such as analysis of covariance (ANCOVA) or multiple regression to statistically control for the influence of extraneous variables on the dependent variable. These techniques allow researchers to isolate the specific impact of the independent variable while holding extraneous variables constant.
For instance, in a study by Brown and Jones (2019) examining the effects of a new drug on blood pressure, researchers used multiple regression to control for potential extraneous variables like age, gender, and baseline blood pressure levels. This statistical control helped isolate the true effect of the drug on blood pressure.
Conclusion
In summary, independent variables are factors manipulated by researchers, dependent variables are outcomes measured to assess the impact of the independent variable, and extraneous variables are unwanted factors that can potentially influence the dependent variable. To control extraneous variables, researchers employ methods such as randomization and statistical techniques like ANCOVA or multiple regression. These strategies enhance the internal validity of research studies by minimizing the interference of extraneous variables and ensuring that observed effects are attributable to the independent variable. As demonstrated by the studies of Smith et al. (2020) and Brown and Jones (2019), these methods are essential tools for rigorous scientific inquiry.