This is a really tricky question. It helps if you've taken a stats course before and have done hypothesis testing. Otherwise, it's just... weird. 😐

The main thing to focus on is the value of p = 0.197 or 19.7%.

With hypothesis testing, we are trying to test some sort of hypothesis (duh?).

There is always a NULL hypothesis and an ALTERNATIVE hypothesis. In the case of a correlation, these would be:

NULL HYPOTHESIS: There is NO correlation between the two variables.
ALTERNATIVE HYPOTHESIS: There IS a correlation between the two variables.

Then, we need to choose a "confidence level" with which we want to be certain of our results. A value of 95%-confidence is pretty popular, and is usually a good place to start if you don't know what to choose. But, if you're given some data (like a p-value or probability-value), you can also look there.

Note that if we have 95% confidence, then we have 5% doubt. Or, if we have 90% confidence, then we have 10% doubt.

Here's the big thing to remember: IF THE P-VALUE IS SMULL, REJECT THE NULL. (I've written it stupidly on purpose).

So, if we set our level of confidence at 80% (which means we have 20% doubt), then we can reject the null hypothesis and conclude that the variables are correlated with each other BECAUSE our p-value is LESS than our doubt value of 20%. Since the p-value is SMULL we reject the null.

😐😑😶🙄

Need a master's degree in stats to do this one... 😫