Language Focus: Data Commentary - By
Transcript
| 00:09 | Hello . You just read a text with many tables | |
| 00:13 | and figures . In this video . We look at | |
| 00:16 | describing data from tables and figures , how a journalist | |
| 00:20 | can tell people what the numbers and figures in an | |
| 00:23 | article mean . We call this data commentary and we'll | |
| 00:27 | look at three things where to find the data , | |
| 00:31 | what it means and moderating a claim . Data commentary | |
| 00:36 | in journalism is important because tables and figures are often | |
| 00:40 | difficult to understand . A figure uses pictures like a | |
| 00:44 | chart or a graph to show information while a table | |
| 00:47 | uses words and numbers . If a reader just looks | |
| 00:51 | at the table or figure , they might not understand | |
| 00:54 | the important information there . Journalists use data commentary to | |
| 00:59 | help readers understand these tables and figures at the beginning | |
| 01:05 | of the data commentary . It's important to let the | |
| 01:08 | reader know which table or figure they're looking at . | |
| 01:12 | We use the structure number of table or figure plus | |
| 01:16 | verb . The most common verb in data commentary is | |
| 01:20 | shows . Other common verbs are presents and illustrates . | |
| 01:25 | So you can begin your data commentary by saying Table | |
| 01:28 | one shows or figure three presents Or figure two illustrates | |
| 01:35 | . You can use any of these verbs with both | |
| 01:37 | figures and tables . Right after you tell the reader | |
| 01:41 | where to find the data , you tell them what | |
| 01:44 | the data means . You want to tell the reader | |
| 01:47 | something interesting about the data . The structure of this | |
| 01:51 | is that plus subject , plus verb plus object . | |
| 01:57 | Let's look at an example of these two things . | |
| 02:00 | Here's some data in the form of a simple figure | |
| 02:03 | . We'll call it figure one . Some people were | |
| 02:06 | asked which politician they liked best . A . Will | |
| 02:10 | be as you can see politician A . Is more | |
| 02:13 | popular with the people than politician B . So we | |
| 02:17 | begin our data commentary by telling the reader where the | |
| 02:20 | data is . Figure one shows . Then we tell | |
| 02:24 | them what it means . Figure one shows that are | |
| 02:27 | subject people our verb like our object politician A more | |
| 02:33 | than politician . B . Let's look at that again | |
| 02:36 | . We tell them where it is . Figure One | |
| 02:39 | shows . Then we tell them what it means that | |
| 02:42 | people like politicians A more than politician B . The | |
| 02:48 | last part of data commentary is moderating a claim . | |
| 02:52 | Let's look at those two words . A claim is | |
| 02:55 | when you say something is true . A good example | |
| 02:58 | is the statement we just made people like politicians a | |
| 03:02 | more than politician B . We're saying that this is | |
| 03:05 | true to moderate . A claim means you don't claim | |
| 03:09 | too much from the data . What you say is | |
| 03:13 | reasonable . You can't make a claim that is too | |
| 03:16 | strong at the moment . Our claim is too strong | |
| 03:21 | , meaning that it is not totally true . Let's | |
| 03:24 | use figure One as an example and give you a | |
| 03:27 | little more data as you can see the people are | |
| 03:31 | young people from the city of Chicago . More of | |
| 03:35 | them prefer politician a politician B but the difference is | |
| 03:39 | quite small , 53 to 47% . The claim we | |
| 03:44 | made earlier was this figure one shows that people like | |
| 03:48 | politicians a more than politician B . We need to | |
| 03:52 | moderate this claim because it is too strong . Do | |
| 03:56 | we have data from all people ? No just young | |
| 04:00 | people , So we need to add that . Do | |
| 04:03 | we have data from all cities ? No , only | |
| 04:06 | from Chicago . So we need to add that . | |
| 04:09 | Was there a big difference in preference for A over | |
| 04:12 | B . No only a little difference . So we | |
| 04:15 | add that . So now our claim is this figure | |
| 04:19 | one shows that young people in Chicago like politician A | |
| 04:23 | a little more than politician B . Now we have | |
| 04:27 | moderated our claim and it is an accurate commentary on | |
| 04:31 | the data . So in this video we looked at | |
| 04:36 | data commentary , we learned how to show the reader | |
| 04:40 | where the data is what it means and how to | |
| 04:45 | moderate a claim . You can test yourself by playing | |
| 04:49 | the data commentary game that follows this video . |
Summarizer
DESCRIPTION:
In this video, we'll look at describing data in tables and figures. This process is how a journalist can tell people what the numbers and figures in an article mean. We call this data commentary. We'll look at three things: where to find the data, what it means, and moderating a claim.
OVERVIEW:
Language Focus: Data Commentary is a free educational video by .
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