Evidence in a debate can be extremely powerful and should be a key element to support an argument.
A famous quote by American statistician, W. Edwards Deming, reads “In God we trust. All others must bring data.”
But too often, data can be misconstrued and misunderstood.
One of the biggest misunderstandings is the difference between causation and correlation.
There are many speeches that share wild, often tongue-in-cheek conclusions as a result of two strongly correlated data sets.
For example, Harvard Business Review looked at the "possibility" that:
- Spending more to see sports matches reduces your likelihood to consume high-fructose corn syrup
- More iPhones sold means more people die from falling down the stairs
Obviously, these are extreme examples, but it shows the dangers of coincidence vs scientific study.
While there may indeed be a similarities between two data sets, some additional vetting is required before a correlation can qualify as causation.
What is the difference between correlation and causation?
Let’s start with the basics - What is the definition of causation versus correlation?
What is correlation?
The Australian Bureau of Statistics provides a great definition of correlation:
“A statistical measure (expressed as a number) that describes the size and direction of a relationship between two or more variables.”
In other words, if you were to plot the data for two variables in the same chart, changes in value in one variable will typically be mirrored by a positive or negative in the other.
Although, correlation does not necessarily mean that there is an actual relationship between these two variables.
Which brings us to causation…
What is causation?
Also known as ‘causality’, the Australian Bureau of Statistics goes on to define causation the following way:
“[It] indicates that one event is the result of the occurrence of the other event; i.e., there is a causal relationship between the two events. This is also referred to as cause and effect.”
In other words, one variable actually impacts the other.
In supporting an argument in a debate, Causation is a better support than Correlation.
Reference: https://www.iperceptions.com/blog/causation-vs-correlation