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Correlation is a statistical method of defining the degree of association between two variables. Hence, the correlation between two datasets tells how much they resemble each other.
When one two variables are being observed at the same time, you are implying a correlation between them. Like when variable 1 is observed, variable 2 is observed too. They either show some change together or show up at the same time.
There are three main types of correlations that are identified:
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Causation between two variables defines that variable 1 has a cause-effect relationship with variable 2. Meaning, variable 1 causes variable 2 or vice versa. The variables causing the effect is called the independent variable and the one getting affected is a dependent variable.
This cause-effect relationship is determined by proper experiments where two groups are made at random from the same. One group is exposed to the treatment and the other isn’t. Depending on how different are the outcomes of both groups, we can define the causes and effects of the variables.
Although correlation means proportional changes in two variables, the change in one variable doesn’t need to be caused by the other. Let’s understand this with an example:
Jack sells woollen clothes. When he collected the data on woollen clothes sales and sales of heaters in his area, he found out that both of their sales are increased and decreased at the same time.
He then concludes that the sales of woollen clothes and heaters are positively correlated to each other.
Although, he couldn’t conclude that increasing sales of woollen clothes causes the increase in the sale is heaters as well. Here, a third variable “winter season” is the regulator of both sales of woollen as well heaters in the area.
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Knowing your research problem and identifying the relationship between the variables is an important task to go ahead with your research. Whether the variables have a cause-effect relationship or their behaviour is just a coincidence, should be cleared out at the beginning.
Example: you are wondering whether the increase in the visits to your websites is due to better SEO blogs. For this, you need to carry out proper tests to determine if it is just a coincidence or causation.