When given a list of numbers, we can use scatterplots to represent the data. Scatterplots can show information about the data through their correlation. It is important to be able to recognize positive and negative correlations in scatterplots, or the lack any correlation. The correlation of scatterplots can give us information about the tendency of the data. Other measures we can use to describe data include along with finding mean, median and mode.
Correlation is an important topic to get straight in your head because it shows up a lot in standardized tests and high school exit exams. But you guys it's not as hard as it sounds, correlation relates to slope if you know what slope is, it's the same idea. Correlation is also tied to trend lines or lines of best fit if that makes sense to you.
Let me show you what I'm talking about, correlation describes the relationship between two variables. So in this first graph, we have what's called a "positive correlation" because as one variable gets bigger the other variable also gets bigger. If you know about slopes you might see that's a positive slope line, easy. Next one same idea negative correlation it's like a negative slope as one variable gets larger like this guy gets larger, this one is getting smaller. As one of them gets larger the other one gets smaller that's called a negative correlation.
Lastly sometimes when we have what we call "no correlation" that's when the dots are just out there in a scattered plot with no real trend you can see. They're like randomly thrown out there. Sometimes variables are not correlated at all, things like how tall you are and what grades you get in school. Those things are totally unrelated to each other, because people who get good grades aren't always tall and people who are tall aren't always getting good grades. Does that make sense? I hope so anyway correlation has to do with how two variables are related to each other. Think of slope might be positive, negative or no correlation at all.