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Guide On Dependent, Confounding And Independent Variable
Variables are characteristics used in research to identify different values. These can be age, species, height, or even exam scores. In scientific research, students often study the effect of one variable in contrast to another one. The cause and effect relationship is determined by the dependent and independent variables in a study.
What Is An Independent Variable?
Do most students wonder what is an independent variable? The answer is straightforward. An independent variable is a characteristic feature of an experiment in psychology. It is often manipulated by researchers and not by other variables in the investigation. For instance, the experiment is about looking at the effects of studies on test scores.
The study will be an independent variable, and test results will be a dependent variable. During the experiment, the examiners will try to figure out if any changes to the independent variable result in any changes in the dependent variable.
Students often have trouble identifying an independent variable. However, this is a variable that stands alone and is not influenced by any other variable in the experiment. An easy way to comprehend dependent and independent variable definitions is by focusing on the cause and effect relationship. The cause is the independent variable, and the dependent variable is the effect.
What Is A Dependent Variable?
Most students have a difficult time figuring out the dependent variable definition. However, it is ideally the variable that is being tested or measured in the experiment. In psychology experiments, researchers try to determine if any changes in the independent variable can affect the dependent variable.
This variable is called dependent because it ideally depends on the variations of the independent variable. However, most students ask, "What is a dependent variable?” as they often get confused with the different types of variables that are involved in an experiment.
To explain this, take an example, where a study is conducted to understand how tutoring can impact test scores. In this case, the dependent variable is the test scores, which are measured and influenced by the independent variable.
Independent And Dependent Variable Example
Variable can be difficult to understand in psychology experiments. Students are often perplexed, and in turn, the whole experiments turn wrong. When they are given assignments to complete on such topics, they feel overwhelmed and, in all probability, look for assignment help services. However, to ease your pain, here are some independent and dependent variable examples.
- An experiment to determine if the sleep patterns of students impact exam scores. This is an independent variable example where the amount of time spent spelling by a student is used to determine their test scores. It can go up and down depending on the span of sleep hours.
- In another experiment, you can compare different brands of towels to see which soaks the most amount of water. Again, as a dependent variable example, it will be the amount of water-soaked by the towel that is dependent on the brand.
- Another experiment can be to determine the effects of caffeine on your appetite. Here the independent variable will be the presence or absence of caffeine that will affect the hunger emotions in a person as a dependent variable.
- Students often get questions like, do tomatoes grow faster in natural, incandescent, or florescent light? Unfortunately, students here fail to understand the variable because there is no direct cause-and-effect relationship. As a result, it becomes tricky to understand the independent variable, which ideally is the type of light, and the plant growth rate is the dependent variable.
Difference Between Independent VS Dependent Variable
Dependent and independent variables are theoretical concepts that can be determined in measurable terms. It refers to the attributes, characteristics, and qualities of an individual, situation, or object that is used in the experiment. As we have already mentioned the definition of the variables, here are some significant differences between an independent variable vs. a dependent variable that can be figured out:
- The value of an independent variable is not dependent on any other variable used in the experiment. However, the value of the dependent variable depends on another variable of the investigation.
- The Independent variable is a presumed cause, while the dependent variable is a presumed effect.
- Independent variables are the regressors or predictors, while dependent variables are predicted variables.
- No observations or mathematical procedures are required for independent variables. However, dependent variables do require these procedures for longitudinal research.
- In a graph, dependent variables are positioned vertically while independent variables are arranged horizontally.
- In an experiment, any change in the independent variable directly affects the dependent variable. However, any independent change variable might not affect the independent variable.
What Is The Use Of Independent Variable And Dependent Variable?
These variables are commonly used in modeling, analysis, statistics, and other science experiments. These variables are self-explanatory, and they provide results precisely as their names suggest. Let us see some common uses:
- In mathematics, the independent variable is the observable input, whereas the dependent variable is considered a detectable output.
- Independent variable in science can be used to determine the different types of species, differences between skin pigmentation, deciding nutrient contents, etc.
- Independent variable in research can be used to determine a diagnostic treatment for a clinical trial or plant growth rate after exposure to light, etc.
Apart from these variables, there is one more type that is not much accounted for. It is known as a confounding variable. This is the type of extra variable that can ruin your entire experiment and give useless results. Most students ask, "What is a confounding variable?" as they try to find any correlation with other variables. However, the attempt is somewhat futile as there is no relation between all these types of variables. This is why it is essential to check on these variables and avoid them to get correct results.
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