1 00:00:00,470 --> 00:00:05,500 Scatter plots are a type of chart that plot points on a grid based on x and 2 00:00:05,500 --> 00:00:07,080 y values. 3 00:00:07,080 --> 00:00:10,840 For example, let's take a look at a sample set of data 4 00:00:10,840 --> 00:00:14,140 with different people's heights and weights. 5 00:00:14,140 --> 00:00:19,490 We can create a scatter plot by selecting the two columns of values we want to plot, 6 00:00:19,490 --> 00:00:23,720 in this case, columns B for height and C for weight. 7 00:00:23,720 --> 00:00:25,190 Let's select those columns. 8 00:00:28,013 --> 00:00:32,237 Gotta hold down SHIFT + CTRL and then go, down arrow. 9 00:00:32,237 --> 00:00:36,230 We've selected the entire data series that we want to plot. 10 00:00:37,310 --> 00:00:42,420 Next I'm gonna use my keyboard shortcuts ALT + N for insert. 11 00:00:42,420 --> 00:00:44,440 Then the scatter plot over here is D. 12 00:00:46,860 --> 00:00:50,310 Scatter, and it's entered up here at the top of the screen. 13 00:00:52,660 --> 00:00:56,970 Sometimes if you have a lot of data in your spreadsheet and 14 00:00:56,970 --> 00:01:00,390 you create a chart, the chart will get inserted off of screen. 15 00:01:00,390 --> 00:01:02,160 So you kind of have to go around and find it. 16 00:01:03,610 --> 00:01:08,522 One tip is to zoom out, so you can go down here and zoom out and 17 00:01:08,522 --> 00:01:13,656 you'll be able to see it right away if you're on a huge sheet. 18 00:01:13,656 --> 00:01:15,360 Let's go back to our normal view. 19 00:01:19,028 --> 00:01:21,610 All right, so looking at the output, 20 00:01:21,610 --> 00:01:26,870 we can see that there does seem to be a correlation between height and weight. 21 00:01:28,890 --> 00:01:30,800 Sort of a linear relationship there. 22 00:01:31,890 --> 00:01:36,790 That's the most common use for scatter plots, identifying correlations in data. 23 00:01:37,890 --> 00:01:41,490 We can actually use a function to determine if there is a correlation. 24 00:01:42,840 --> 00:01:46,020 You should be familiar with spreadsheet functions already. 25 00:01:46,020 --> 00:01:47,690 If you didn't take the prerequisites for 26 00:01:47,690 --> 00:01:49,800 this course, I'd recommend you do that now. 27 00:01:50,830 --> 00:01:54,250 I've added a link to the prerequisite content in the teacher's notes. 28 00:01:54,250 --> 00:01:55,265 If you need a refresher, 29 00:01:55,265 --> 00:01:59,575 I've also linked to the stage where we specifically cover functions. 30 00:01:59,575 --> 00:02:03,555 Why don't you try and figure out how to calculate the correlation of height and 31 00:02:03,555 --> 00:02:05,315 weight in this data set. 32 00:02:05,315 --> 00:02:07,325 And in the next video, I'll show you how to do it.