Correlation and Causation are closely related to one another. However, certain studies state that these two variables do not imply in a relationship. This paper discusses the major contrast between correlation and causation and its effects. The first paragraph concerns the concepts of the two terms; correlation and causation. Secondly, cause and effect relationship is analysed. Finally, detailed analysis is provided to understand the relationship between correlation and causation.Moreover, the distinction between two terms can be understood easily by their definitions.
Correlation
According to Jaffe (2010), correlation refers to the association between two or more variables. For instance; there is a strong relationship between advance technology and smartphones. Researches indicate that correlation involve statistics and arithmetical dimension. It ranges from positive 1, negative 1 and zero correlation. A positive correlation is when both variables tend to increase, for example; tall people have heavy body weight. Negative correlation determines negative relation. More precisely, it is defined as association of variables when one increase and other one variable decreases. For instance, the relation between an altitude of sea and degree of temperature; going above the mountain comprise on coldness. Thus, height tends to increase when going up while, temperature get decreases. However, zero correlation defined as no association among the variables, for instance; coffee and intellect are two different variables having no association with each other.
Studies indicate that correlation does not undergo research methods, but it is a statistical way where data is gathered and analysed. It may be useful, for instance; knowing the relation among viewing violence on television and propensity of violent attitudes amongst youngsters.
In addition, correlation techniques are generally catered in intelligence study, for example; researchers tend to test and find the relationship between the IQ level and strength or weakness of particular identical twin-brothers and non-identical brothers.
Researcher investigates variables whether they are ethical or unpractical by correlational statistic. And through correlation graphical form, researchers are able to see clearly about relationships of variables.
Causation
A casualty does not entail correlation and association. According to Psychology dictionary, causation indicates that ‘a cause retain potential aptitude to inculcate an effect’. It demonstrates the effect of one variable over another variable. For instance; as stated above, viewing violence on television can cause aggression among youngsters. Another example would be, by clicking on email cause to move on a website or smoke causes cancer.Finally, climbing towards rock face will definitely cause physical injury.
Cause and Effect
Cause and effect terms are significantly used in psychology and study of other science disciplines. Cause and effect relationship establishes when on incident i.e. cause creates happening of another incident i.e. effect. For instance; waking up from the loud noise of alarm; in this circumstance, the alarm is a cause that effects on waking up a person. There are several effects of one cause. For example, reckless driving can cause an accident, damage to the own car, or breaking the traffic rule.
Psychologists conduct not only researches but experimental methods to classify whether there is ‘effect’ of one variable over another or if one variable ‘cause’ any change on another.Additionally, the cause is an independent variable, whereas the effect is dependent. For instance; when reckless driving (cause) take place, it leads to accident or car damage (effect).
Relationship between Correlation and Causation
According to Shuttleworth (2008), correlation and causation principle is significant for researcher and scientist. However, this principle is also expedient for students who are learning politics, media sciences, or marketing majors.
Considering the example of smoking, a survey posted in a British magazine implies on the behaviour of teenagers in which they were asked whether their parents smokes or not. Results of the survey exhibited that two variables correlates with each other, and there is the severe effect of paternal smoking on the behaviour of children. And children misbehave if their parent smokes. In other words, paternal smoking causes disobeying among their children.
Additionally, the correlation may be analytical and symbolic of causality. According to Bechtel (2013), the correlation tends towards prediction, for instance; the association of chain-smoking and cancer allows the person to predict that continuous smoking engage towards severe heart-attacks or mouth cancer. On the other hand, Causality tells the ways about how the effect could be change, for example; knowing about chain smoking causes cancer that leads to death allows a person to take curable actions such as quitting smoking.
The main objective of conducting correlation is to evaluate associations between two or more variables. Advantages of correlation include a test of anticipated relations among variables to make predictions. It can be used to evaluate relationships of daily life dealings. However, the correlation has a drawback as it is cannot be useful to create interventions among associative variables.
Conversely, the main objective of causation is to evaluate the causative effect of one or more than one tentative handling over dependent variables. Advantages of causality involve the depiction of conclusions of casual associations between variables. On the other hand, causality does not involve tentative handlings of variables. It can take long time and can be costly.
Many studies suggested that correlation does not integrate with causation. It means that if two variables associated with each other, it does not cause any effect on each other. For instance, on seasonality measures; US citizens tends to pass more time in shopping malls during spring and winter seasons whereas, lesser time during summers so, it does not mean high shopping become frantic during winters. In other words, wintery season relates to Christmas eves and sales of New Year but it does not have a precise effect on sales. Moreover, studies indicate that correlation does not entail causation. This means, it cannot be assumed that one variable cause-effect over another if there is a strong relation between variables. For instance, if there is positive association among viewing violence on television and violent attitudes in teenagers. Both can become a cause of third variable, for example; aggressive behaviours at home. Additionally, the researcher could not go away from the data through correlational stats.
Moreover, it is not necessary that correlation entails causality, and two or more variable can associate with each other deprived of casual relation. A correlation has some limitations, but it is also useful and significant to study science.
Conclusion
Correlation refers to the affiliation between two or more variables. For instance; there is a strong relationship between online shopping and smartphones, or tall people possess heavy weight.Researchers indicate that statistics and arithmetical dimension are involved in correlation. On the other hand, causation determines the effect of one variable on another variable. For instance, smoking cause cancer that leads to death or television violence causes aggression in teenagers. Researchers conduct correlation in order to evaluate associations between two or more variables that results in making predictions. Relationships of daily life can be assessed through correlation. However, causation’s main objective is to evaluate the effect on one or more variables through experiments and handlings. Studies indicate that correlation does not undergo research methods, but it is a statistical way where data is gathered and analysed. On the other hand, causation undergoes experimental methods and conceptual techniques.
In addition, both terms undergo weaknesses; correlation has a drawback as it is cannot be useful to create interventions among associative variables. While causation could be costly and time taking.
In psychology, cause and effect terms are used significantly. The relation exhibited when a cause (Such as rash driving) occurs that leads to the injurious effect (such as car damage or accident). Another example would be traffic lights when they blink; cars are ready to start and go. Here, traffic lights are the cause to run the cars.
Causation segregates and controls independent variables to know its impact over the dependent term. It also controls the atmosphere to eradicate unnecessary variables. And this causation creates cause and effect relation. Conversely, the correlation looks for variables and classifies relations and the association between them.
In causation, there is a test of independent variable upon dependent variable to know the effect, whereas correlation comprises connections among two or more variables. Therefore, both terms are dissimilar in a way that; causation is used to predict cause and effect relation while, the correlation could only foretell associations among variables. In addition, correlation moves in the direction of prediction whereas, causality tends to make a change when negative effects occur.
References
Bechtel, B. (2013). Correlation and Causation. Causation: terminology and the logic of casual research.
McLeod, S. A. (2008). Correlation.Simply Psychology. Retrieved April 19, 2015 from http://www.simplypsychology.org/correlation.html
Shuttleworth, M. (2008). Correlation and Causation. Explorable (think outside the box).Retrieved Apr 17, 2015 from https://explorable.com/correlation-and-causation
