In experimental research, variables are the specific characteristics or factors that are manipulated and measured in order to test a hypothesis. These variables are carefully controlled and manipulated in order to observe the effect on the outcome or dependent variable. For example, in a study examining the effect of a new drug on blood pressure. The independent variable would be the drug and the dependent variable would be blood pressure. The researcher would manipulate the dosage of the drug and measure the corresponding change in blood pressure.
Non-experimental research observes variables in their natural state instead of manipulating them. The researcher does not have control over the variables and cannot manipulate them. Instead, the researcher observes and measures the variables as they naturally occur in the population. For example, a study examining the relationship between income and education level would not manipulate either variable. But instead, observe and measure the levels of each variable in a sample of individuals.
One of the main differences between experimental and non-experimental research is the level of control the researcher has over the variables. In experimental research, the researcher has complete control over the independent variable and can manipulate it to test the hypothesis. In non-experimental research, the researcher does not have this level of control and must rely on observations and measurements of naturally occurring variables.
Another difference is the causal relationship between the variables. Exercising a high degree of control in an experiment helps eliminate alternative explanations for the change in the dependent variable, thereby establishing a causal relationship. However, in non-experimental research, it is not possible to establish a causal relationship because other variables may be influencing the outcome.
Quantitative Research Designs: Non-Experimental vs. Experimental
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