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Correlation vs Causation: Let's End the Confusion Once & For All!

17 Nov 2021 735 8 minutes
Correlation vs Causation

Correlation vs Causation: Let’s End the Confusion Once & For All!

Correlation vs Causation, two terms that are relevant but miles apart when it comes to similarity. Students studying management and business studies, or who plan to create a digital product that they can introduce one day as their own must know about the key differences between the two. Students also get assignments based on the differences between these two which in itself is enough to represent the impact of the topic. The professor put great emphasis on these concepts because they are aware of how things work in the corporate world. While professors feel that it is for the betterment of the students, the feeling is not mutual on the other side. Scholars find it stressing and confusing to work with these concepts as the difference is not known to all of them.

If you are a student struggling with the concepts and want a simple answer, this blog will help you find it out. In this post, we will discuss the causation vs correlation definition. We will also take a look at some of the differences between the two and how you can remember all of them. Without further ado, let us begin the blog with the definition of both these terms. Shall we?

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What is Correlation? Defined With Example

As the name suggests, the relation between two entities or events that occur with a single incident is called the correlation. A lot of students read this single sentence and believe that they have understood the concept. Well, that is where they go wrong, as correlation is not that simple.

The correlation is technically defined as the degree of relationship between the two occurring processes. Now, to be clear from the very beginning, correlation never means causation. For instance, suppose there are two entities X & Y. If you have applied an operation on X and in the result Y is also affected or noticed to change, it clearly shows that they both are related. However, this in no way means that the operation on X caused the change in Y, and hence it is not causation.

The best correlation vs causation exampleto understand the correlation, as per our experts is -

"In a study, it was seen that the number of cell phone users increased, the number of cancer patients also increased. Many statisticians saw it as causation where cell phones were causing cancer however when the data was put together, it showed that it was just a correlation that can be made between a lot of entities. For instance, the number of social media users has also increased as the number of cancer patients increased that does not mean that cancer had caused the increase in social media users, does it?".

With the above logical example, it can be seen that some things can correlate, but it never means that they are causing changes in each other.

As far as the types of Correlations are concerned, there are 2 major ones that you must keep in mind -

  1. Positive Correlation
  2. Negative Correlation

We will not go into the deeper layers of correlation as it might turn the blog into a class. If you need more information, feel free to check out the samples, or better, call our experts with your queries. Now that you have understood correlation, let us take a look at causation in the next section.

Causation: Defined With Example

Have you ever heard of cause and effect connection? If yes, the concept of causation will be a piece of cake for you, and if not, there is no need to panic. To define in brief, cause, and effect is the relation between two entities in which one entity causes a change and the second one is affected.

Now as per the above explanation of cause and effect connection, causation can be defined as the entity that is related and causes a change to the related entity when anything occurs. In simple words, X causes Y. It means that events X and Y occur together, and not only do they occur together, but one of them is causing the other.

Example - The best example of this phenomenon can be the working of a smartphone. If the battery of the smartphone dies, the video you were watching on it will not work as it will be switched off. Now, the battery of the smartphone is causing the shut down of the smartphone, which means X is causing Y. You can understand the correlation from it as well. The phone got off, and the video player stopped. Both the incidents were co-related but not caused due to each other.

It is clear by now that both correlation vs causation are similar yet different. There can be so many applications of these concepts in your studies, and thus you must stay clear of all the confusion related to them. For those who do not understand it yet, or need assistance in clearing the pilled-up documents, make sure you read the next section, as it has great advice for you!

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Still Confused Between Correlation vs Causation? Let the Expert's Handle It!

That was all about correlation vs causation. As you might have got an idea the similarities between the two concepts are uncanny and that is why students get confused and lose their marks. The experts have tried to give you a brief idea about the concepts with an example to help you understand the differences as well as the definitions of the terms. If you feel that the knowledge that you have acquired is not enough for finishing the papers that you have, you can simply reach out to our experts as they have detailed information on every type of document that you may get assigned.

It does not matter if you are pursuing your bachelor's or a Ph.D. in digital products, no matter what level the problem that you have, our experts have the answers for you. Other than that students can also avail research paper help, math assignment help and all types of assignment assistance to assist you out. So what's stopping you now?

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