All language subtitles for 04 - Add trendlines to charts

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These are the user uploaded subtitles that are being translated: 1 00:00:00,004 --> 00:00:01,007 - [Curtis] Whenever you collect data 2 00:00:01,007 --> 00:00:03,009 in Microsoft Excel or another program, 3 00:00:03,009 --> 00:00:06,004 you should always examine it for trends. 4 00:00:06,004 --> 00:00:07,002 In this movie, 5 00:00:07,002 --> 00:00:09,009 I will show you how to examine your data visually 6 00:00:09,009 --> 00:00:12,006 by adding a trend line to a chart. 7 00:00:12,006 --> 00:00:16,001 My sample file is 02_04_trendline. 8 00:00:16,001 --> 00:00:18,003 And you can find it in the chapter two folder 9 00:00:18,003 --> 00:00:20,007 of the Exercise files collection. 10 00:00:20,007 --> 00:00:25,006 In this workbook, I have a worksheet with a table of data. 11 00:00:25,006 --> 00:00:27,006 And I have the distance 12 00:00:27,006 --> 00:00:30,003 that a customer traveled to get to your store 13 00:00:30,003 --> 00:00:34,002 and then the amount that they spent once they were there. 14 00:00:34,002 --> 00:00:35,005 And if I scroll down, 15 00:00:35,005 --> 00:00:38,000 you can see that the customer who traveled 16 00:00:38,000 --> 00:00:45,008 the farthest came from 152 miles away and spent $195. 17 00:00:45,008 --> 00:00:47,009 I've already created an XY scatter chart 18 00:00:47,009 --> 00:00:51,006 to show the relationship between distance and amount spent. 19 00:00:51,006 --> 00:00:55,006 And you can see that there is a fairly clear relationship. 20 00:00:55,006 --> 00:00:59,003 If you want to find a line that best fits the data, 21 00:00:59,003 --> 00:01:02,001 you can add a trendline to your chart. 22 00:01:02,001 --> 00:01:05,002 To do that, I will click the body of the chart. 23 00:01:05,002 --> 00:01:10,003 And then on the Chart Design contextual tab on the ribbon, 24 00:01:10,003 --> 00:01:15,006 I will go to the far left and click Add Chart Element, 25 00:01:15,006 --> 00:01:19,009 and then point to trendline, and then click Linear. 26 00:01:19,009 --> 00:01:22,002 That's because I know that the data 27 00:01:22,002 --> 00:01:24,009 in this particular dataset is linear. 28 00:01:24,009 --> 00:01:26,009 So I'll go ahead and click that. 29 00:01:26,009 --> 00:01:28,006 And I can see the trendline. 30 00:01:28,006 --> 00:01:30,003 And in this case, 31 00:01:30,003 --> 00:01:33,002 it turns out that the trendline intersects 32 00:01:33,002 --> 00:01:38,001 almost exactly with the last data point in the set. 33 00:01:38,001 --> 00:01:39,006 That doesn't usually happen. 34 00:01:39,006 --> 00:01:43,001 So if it doesn't for your data, don't worry about it. 35 00:01:43,001 --> 00:01:47,001 So what this trendline tells you is that an individual 36 00:01:47,001 --> 00:01:52,004 who travels approximately 120 miles is likely to spend 37 00:01:52,004 --> 00:01:57,008 a little bit over $150, probably very close to 160. 38 00:01:57,008 --> 00:02:00,003 Where if they traveled 60 miles, 39 00:02:00,003 --> 00:02:07,004 they will most likely spend about 85 to $90. 40 00:02:07,004 --> 00:02:08,003 And again, 41 00:02:08,003 --> 00:02:12,003 this is a line that is designed to show you the trend, 42 00:02:12,003 --> 00:02:15,003 even though some values are going to be far from the line. 43 00:02:15,003 --> 00:02:16,005 And you can see for this point 44 00:02:16,005 --> 00:02:20,001 where someone traveled 100 miles and spent $200, 45 00:02:20,001 --> 00:02:21,003 that's far from the average. 46 00:02:21,003 --> 00:02:22,008 So they spent more than expected, 47 00:02:22,008 --> 00:02:24,000 but another customer who traveled 48 00:02:24,000 --> 00:02:27,003 about the same distance spent less than expected. 49 00:02:27,003 --> 00:02:30,003 If you want to change the format 50 00:02:30,003 --> 00:02:32,007 or appearance of your trendline, 51 00:02:32,007 --> 00:02:37,002 you can go to the Chart Elements control, 52 00:02:37,002 --> 00:02:38,005 point to Trendline, 53 00:02:38,005 --> 00:02:41,001 and then click the arrow that appears to the side, 54 00:02:41,001 --> 00:02:43,003 and then click More Options. 55 00:02:43,003 --> 00:02:46,005 That opens the Format Trendline task pain. 56 00:02:46,005 --> 00:02:48,005 And you can change elements 57 00:02:48,005 --> 00:02:51,003 of it such as, for example, forecasting. 58 00:02:51,003 --> 00:02:53,009 In this case because we don't have time series data, 59 00:02:53,009 --> 00:02:56,008 it doesn't actually make sense to use a forecast 60 00:02:56,008 --> 00:02:59,006 for values outside of your data range. 61 00:02:59,006 --> 00:03:02,005 We have collected data on individuals who traveled 62 00:03:02,005 --> 00:03:05,006 up to 150 miles to get to your store. 63 00:03:05,006 --> 00:03:08,000 And the question is, if this trend holds, 64 00:03:08,000 --> 00:03:11,004 if someone travels say 300 miles, 65 00:03:11,004 --> 00:03:15,002 would they actually spend $400 typically? 66 00:03:15,002 --> 00:03:16,007 That doesn't seem likely. 67 00:03:16,007 --> 00:03:18,002 And that's a sort of judgment 68 00:03:18,002 --> 00:03:20,001 you have to make about your business. 69 00:03:20,001 --> 00:03:20,009 So even so, 70 00:03:20,009 --> 00:03:24,000 you should limit your predictions to the dataset 71 00:03:24,000 --> 00:03:26,004 and data range that you have. 72 00:03:26,004 --> 00:03:28,004 If someone travels 160 miles, 73 00:03:28,004 --> 00:03:30,003 even though it's more than 152, 74 00:03:30,003 --> 00:03:32,008 you can probably make reasonable assumptions 75 00:03:32,008 --> 00:03:35,000 about how much they're going to spend. 5867

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