Simply put, the covariance tells us if two variables such as the ones presented in this video's main example move in the same direction. Among other things, we use the covariance to calculate the correlation coefficient, which also tells us to which degree the two variables move together (but more on that in a future video... for now, we'll focus exclusively on explaining the covariance). In this video, we take things one step at a time so as to explain the covariance properly. On the one hand, we start with the definition of the term accompanied by examples and on the other hand, we also try to meaningfully understand the covariance formula. Like with many other statistics terms, wrapping your head around the covariance is quite difficult if it is not explained to you properly, with your professor simply shoving a formula down your throat. However, if you take the time to understand the covariance logically and in a way which ensures you won't forget all about it by next week, you'll realize it's actually not that difficult. A definition here, a formula there and some carefully-chosen examples sprinkled in: bam, you now understand the covariance and will actually be able to explain it to others in a non-cringeworthy manner. All it takes is... you've guessed it: one minute of your time :)