We're talking about the connection between two things, which in the world of psychology we call a "correlation". It's a lot like figuring out if eating more chocolate 🍫 makes you happier 😊 (Spoiler Alert: It totally does, but don't quote me on that!)

The "correlation coefficient" is a fancy term for a number between -1 and 1 that shows how strong the connection is. The closer it is to -1 or 1, the stronger the link, and this is what we call the "effect size". Think of it like the size of a party 🎉: a bigger number means a bigger party, hence, a stronger link!

But hold your horses! It's not just about the party size, we need to know if it's an epic party or just some random get-together. This is where statistical significance comes in.

Statistical significance" is like the likelihood that you'd have a blast 🥳 at this party just by chance. So, if you take a small group of people and find a strong link, there's a higher chance it's due to randomness. But if you get the same link in a larger group, you can be more confident that it's a genuine connection, not a fluke.

We have these cool little cut-off points (thanks to our friend Cohen in 1988) to decide if something is significant or not. It's kind of like judging if a movie 🎥 is good based on its Rotten Tomatoes 🍅 score. Here's a quick cheat sheet:

More than 5% (p = n.s.): The link is non-significant. Like that movie with a 20% Rotten Tomatoes score, it's not great.

Less than 5% (p < .05): The link is statistically significant. It's like a movie with an 80% score, pretty good!

Less than 1% (p < .01): The link is very significant. We're in the 90% range, that's an Oscar-worthy film right there.

Less than 0.1% (p < .001): The link is highly significant. This movie is the next "The Godfather", absolutely fantastic!