Welcome to our lesson on scatter plots. A scatter plot is a graph of plotted points that shows the relationship between two sets of data. There are many types of relationships that could be distributed into a scatter plot. You could have a positive linear relationship showing that as X is increasing, Y is also increasing. You could have a negative linear relationship which shows that as X is increasing, Y is decreasing. You could also have a scatter plot that shows absolutely no relationship that there is no pattern that points are just scattered all over the graph. You can also have a scatter plot that shows non linear relationships. You’ll learn about these more in algebra 1 you can see that there’s a curve, so they’re nonlinear because they don’t form a line, so these are special types of functions. This is part of a quadratic function and this is part of an exponential function. You’ll learn about those in algebra 1 so let’s see if you can match these data sets, we have data a data. B and Data C and we have three graphs graph, D graph, E and graph. Now I’d like you to see if you can read through the data and imagine which graph would correspond to that data. If you had actual numbers, go ahead and pause when you’re back, ready to come back and check your work hit play. Welcome back so first, let’s look at the graph. D that would model the data from B. The number of siblings a person has in their age. There’s an absolutely no correlation between the number of sisters and brothers that you have, and your age graph II will show the number of hours. You drive and the number of miles you travel, so the more hours you drive. There are more miles that are covered that would show a positive linear relationship. Both data sets increase rep. F would be data a the age of your car as your car is increasing in age the number. Um, the value of your car is decreasing, so Y would be the value of your car. X would be the age of your car. And there would be a negative linear relationship. You’ll be asked to make scatter plots. Here’s some data that was collected from students, the number of hours that they studied or quiz in their quiz score. So I graph the data to see. If there was any correlation, you can see that I have a cluster here. There’s three data points here. Where’s all the other debris spread out? You can see. I have an outlier here. Somebody studied five hours and scored a 35 where everybody else was pretty much right along here, and you can see that this is trending in a positive linear relationship, so I can conclude that the number of hours their studied the higher. Your quiz score will be. Here’s how we interpret a scatter plot. This scatter plot shows the seasons of a Netflix series. This shows the millions of viewers that are watching and this is the season so you can see that as the seasons go on, they lose viewership. I’d like you to think about these two questions. Go ahead and hit pause. Look at the graph in answer the questions come back and hit play when you’re ready to check your work. Welcome back, so question. One about how many viewers watched three seasons so I would go up to the season three, and then I go to that data point and I go over and I’m gonna conclude that it’s about twenty five million viewers. We don’t know exactly because there’s an interval of four here, so if you said 26 that would be acceptable just as long as you’re using the word about so people know that you are approximating question. Two about 32 million bit watched up to how many seasons, so let’s go over to 32 and down to a data point and we can say that season 1 was watched by 32 million viewers, So I’d like you to describe these relationships as positive, linear, negative linear or no correlation. Go ahead and hit pause, read through the relationships and come back and hit play when you’re ready to check your work. Welcome back So the temperature outside and the air conditioning cost would model a positive linear relationship as the temperature outside would be increasing, the cost of air conditioner would be increasing the amount of screen time in a week And your shoe size no relationship. The amount of screen time people have in a week, has no correlation to the shoe the size that they wear the amount of gas in your boat. In the time spent waterskiing would show a negative linear relationship, the more gas you used the more time you would have spent. So as the time is increasing, the gaps in the boat is decreasing and that would show a negative linear relationship. Thank you for joining me today.