1 00:00:00,400 --> 00:00:04,110 In Excel, trend lines are used in the scatter plots, and 2 00:00:04,110 --> 00:00:08,130 they show the general direction that the points of a scatter plot are going. 3 00:00:09,270 --> 00:00:10,940 Let's add a trend line to the Height and 4 00:00:10,940 --> 00:00:14,320 Weight scatter plot we made earlier in this course. 5 00:00:14,320 --> 00:00:19,440 So, you've probably guessed correctly that we're gonna go back to the Design section 6 00:00:20,720 --> 00:00:22,930 of the ribbon and add a chart element. 7 00:00:24,240 --> 00:00:26,270 And down here is Trendlines, lets do Linear. 8 00:00:27,760 --> 00:00:32,700 The slope of the trendline will signal the strength of the correlation of the x and 9 00:00:32,700 --> 00:00:33,720 y variables. 10 00:00:34,800 --> 00:00:36,740 Let's make our trendline a little bit thicker. 11 00:00:38,210 --> 00:00:42,176 I'm gonna click on it, to select it, then I'm gonna right click it and 12 00:00:42,176 --> 00:00:44,106 scroll down to Format Trendline. 13 00:00:44,106 --> 00:00:49,279 And I'm gonna go to the Line section and increase the Width. 14 00:00:51,999 --> 00:00:55,645 And to make it stand out a bit more, I'm gonna make it black, 15 00:00:55,645 --> 00:00:57,730 because the data points are blue. 16 00:00:58,940 --> 00:01:03,290 So again, the slope with a trendline will signal the strength of the correlation of 17 00:01:03,290 --> 00:01:04,060 the variables. 18 00:01:05,418 --> 00:01:09,030 If the trendline is sloping down from left to right, 19 00:01:09,030 --> 00:01:12,920 that means that is some degree of negative correlation. 20 00:01:12,920 --> 00:01:15,550 If it is sloping up from left to right, 21 00:01:15,550 --> 00:01:18,150 that means there is some degree of positive correlation. 22 00:01:19,180 --> 00:01:22,050 So here, based on this hypothetical data set, 23 00:01:22,050 --> 00:01:27,710 if someone is 60 inches tall, we'd expect their weight to be 120 pounds. 24 00:01:27,710 --> 00:01:31,200 This is all hypothetical obviously, but 25 00:01:31,200 --> 00:01:35,950 adding a trendline can help your audience realized what data points are below or 26 00:01:35,950 --> 00:01:39,100 above what we'd expect them to be very quickly.