Quantitative: Non-Experimental Approach
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Quantitative: Non-Experimental Approach
The non-experimental approach is used to test the differences and relationships among variables. The independent variable in this approach are not manipulated, subjects are not assigned at random, the design lacks a control group, and it offers level IV evidence (Polgar & Thomas, 2011). The researcher does not have a direct influence on the participants in the experiment. A researcher can be interested to know whether there is any relationship in the health of babies and smoking. This article will focus on explaining why such situations require a non-experimental approach.
The variables of interest, in this case, would be the effect of smoking and age of babies, none of which can be controlled. Non-experimental designs are quantitative, and as such, they depend on quantitative data and other variables that can be quantified numerically (BC campus, 2019). A sample size of about thirty participants or sources of information is often required to reduce the sampling errors and normalize the shape of the distribution. Non-experimental research includes predictive, descriptive, comparative, correlational, and causal-comparative (Blalock, 2018).