Correlation vs. Causation: Why it Matters while using Jointly
It’s important to understand the difference between these two concepts to get the most out of Jointly. Let’s start with a quick refresher on both concepts.
Correlation is the relationship between two sets of variables used to describe or predict information. For example, the more time you spend running on a treadmill, the more calories you will burn.
Causation (also known as cause-and-effect) exists when an event or action appears to have caused a second event or action. For example – I bought a new bed comforter and placed it in my washing machine to be cleaned. After cleaning the comforter, my washing machine stopped working. I may assume that the first action, washing the comforter, caused the second action, broken washing machine.
A specific example
These two terms are often confused, which makes it difficult to accurately assess whether or not a cause-and-effect relationship has truly occurred.
Let’s say Herb has a coin. As he flips it, he says aloud, “heads.” He gets a heads. Then he flips it again and says, “heads.” And again he gets a heads. Is he causing the coin to land on heads by calling it? Of course not. But, if he did it 20 times in a row – then we might start to wonder how he’s doing it. But we still wouldn’t think he was causing it with his words, because that doesn’t stand up to reason or physics. Maybe he’s got a trick penny or a specially trained technique. So, Herb’s calls and results are perfectly correlated. But something else is causing them.
Jointly can help you identify products that may be effective at helping you achieve your goals, based on the real experiences of other people like you. But everyone has a unique endocannabinoid system, so you can’t be sure that a product that works well for one person will work the same way for you.
Jointly gives you the tools to find out for yourself what is working for you and what isn’t, determine your optimal dose, minimize any side effects, and learn how the quality of your cannabis experience can be impacted by sleep, hydration, exercise, diet, and more.
That’s great. But, if you mistake correlation for causation, it can impact the quality of your experience. How?
As you submit reports in Jointly, you’ll start to see patterns emerge in your Learning Center. Perhaps you’ll start to see that you’re getting better results with 10mg of your favorite gummy instead of 15mg. Perhaps you’ll discover that you experience more anxiety when you use cannabis alone compared to when you are with friends and family. Perhaps you’ll start to see that you have better results when you wait at least 12 hours between sessions.
As these patterns emerge, you should treat them with a healthy skepticism. Are you seeing correlation? Or causation? Do you have enough data points to draw any conclusions yet? It’s not easy to make these determinations, but the more reports you submit – the more meaningful the results will be – especially if you are mindful of cognitive biases that may impact the quality of your results.
Good luck and we wish you well on your journey.