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Causal logic, “common sense”, would claim that one variable or behavior/s will result in
the consequence of that particular circumstance. Thus, the independent variable would be the
individual’s behaviors in reaction to a simulating situation; resulting in per say, unwanted
physical contact of another. The consequence would be a law violation: subjecting the violator to
the criminal justice system. Correlation is said to be the manipulation of the dependent variable
as a result of the independent variable changes. Examples of its use consist of relationship
measurement through either qualitative and/or quantitative research; however, combined research
provides the observer with multiple perception and interpretations of understanding the data
(Schaefer, 2012, pp. 28-32).
The main similarities between casual logic and correlation could be observed within their cause
and effect relationship; variable dependency. Correlation explains the relationship; two or more
variable, in which things are mutual or complementary as were causation define the cause and
effect of such variables. Establishing relationships allows researchers to developed measurable
variables for presuming, forecasting, and testing of ideas or hypotheses. The importance is in
establishing the link along with the evaluaon of potenal negave impacts. Both methods provide
research with the ability to semi eecvely test theories if gathered data is sciencally obtained.
Reference
Schaefer, R. T. (2012). What Is the Scienc Method? In R. T. Schaefer, Sociology: A Brief Introducon (pp.
28-32). New York, NY: McGraw-Hil.

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