Distinguishing correlation from causation is one of the most frequent mistakes made in reasoning.
These two words appear deceptively similar but identifying the difference between both can either make or break the process of creating a high-value product for your customers.
Let’s dive right in as I review correlation vs causation psychology and describe the main differences between these two common terms.
What is Correlation?
Correlation is a relationship or connection between two or more objects. This relationship is not caused by chance. This term, used most often in statistics, refers to the degree of connection between any random variables.
If X and Y, two variables, tend to be observed at the same time, there’s a correlation between them. You cannot say X caused Y, you will simply say that when X and Y are observed together.
Bottom Line: Correlation answers whether or not 2 things will happen at the same time. It doesn’t imply causation. Sometimes, correlation can be referred to as a coincidence.
Causation is the principle of a connection or a relationship between effect and its causes. It implies that X & Y have a cause-and-effect relationship with each other.
Bottom Line: Causation answers why 2 things or events will happen at the same time.
Let’s begin this section with Correlation vs Causation Graph:
As you can see in the graph above, there is a correlation between the amount of ice-cream consumed and the number of people who died because of drowning.
Now, I’d sound ridiculous if I say that ice-cream consumption causes drowning, wouldn’t I?
In fact 'Summer Weather’ is the third variable, which is the causative agent in this scenario.
In warm weather, people tend to consume more ice-cream and also swim more often, which leads to an increase in the number of drowning deaths.
We can apply the same distinction to SEO results. At Troop Messenger, we run an SEO analysis before writing any blog post. We do this analysis for a high number of factors, as we try to identify a correlation between those factors.
This allows us to review whether or not two different factors are changing in the same direction, at the same time, and also understand the influence level they have on each other.
A change in your website’s SERPs ranking could be due to causation or correlation with any of these factors:
Your SEO efforts
On-page optimization metrics
Google’s Algorithm updates
The difference between these two terms must be taken into consideration during SEO analysis, especially when trying to find causality among different factors.
Before judging the events, try to view them from different perspectives. While studying the SEO factors, develop more understanding about the relationships between events.
You might think that there is a correlation between higher rankings and a large amounts of links. But, after a proper analysis, you’ll be able to distinguish it as a causality.
As you continue working more within this field, you’ll be able to assess and distinguish both these situations better.
If you want a bigger and better perspective, you’d need to review tons of data. In the section below, I’ve explained 3-Steps of generating meaningful data by tracking a few metrics.
Track Your Keywords
Track On-Page Changes
Track the Links
Track all social Signals
So what have we learned from the correlation and causation definition and examples? These two deceptive terms are simply one of the common ways of testing whether two (or more) variables have an effect-and-cause relationship or they are simply correlated to one another.
Are there any other correlation and causation examples you’d like to hear more about on the Troop Messenger blog? Is there correlation vs causation analyses that you’re interested in within the broader realm of digital marketing and search engine optimization? Let us know in the comments.
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