Wednesday, September 5, 2007

Independent and Dependent Variables

By Sudipa Sarkar
Describe the difference between the independent variable and the dependent variable in an experimental study. Propose an example of a study and identify the independent and dependent variable. Address some of the challenges in keeping everything except the independent variable constant in a study and why is this important? Give an example of how experimenter bias might threaten the validity of your sample study.

In an experimental study comprises of two variables:-

• The Independent Variable (IV) and
• The Dependent Variable (DV)

While designing an experiment, an independent variable is defined as a variable that can be manipulated or chosen by the experimenter to identify its relationship with an observed phenomenon (dependent variable). The independent variable is also known as the manipulated variable, exposure variable, predictor variable, x-variable or explanatory variable.

On the other hand, dependent variable is such a factor whose value is varied in accordance with other variable (independent variable). While performing an analysis, the researcher generally focused to find out the reason behind the varying value of dependent variable in different settings and hence, compared. This variable is also known as response variable or y-variable.

For example, if a researcher wants to examine whether a particular therapy has an outcome on a group of individuals, he must assign the therapy as an independent variable and the group of individual to dependent variable. Again if a researcher examines the relationship between the dosages of drugs on the severity of symptoms of a particular disorder, he may measure and analyze the frequency and varying intensity of symptoms (dependent variable) while altering the dosages (independent variable). Hence, it can be concluded that the independent variable can be manipulated throughout the research process and it has some effect on the dependent variable.

Keeping the independent variable constant in a study is significantly important because it serves the purpose of the experimental investigation of causality by the virtue of drawing conclusion on the effect of changes in the values of independent variable on a dependent variable. As the value of independent variable is predetermined, it helps to identify the effect of differences in independent variables on the behaviour of dependent variables.

Experimenter bias is characterized by the errors in research study originated as a result of beliefs of the experimenter influencing the outcome of the experiment. An example of experimenter bias includes researcher responses more positively with the subject when the subject fulfils the researcher’s expectation or acts according to the expectation such as reporting relaxed during an experiment on relaxation technique may result the researcher to employ positive reinforcement bias like smile.
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1 comment:

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