Hello, you just read a text with many tables and figures.
In this video, we'll look at describing data from tables and figures.
How a journalist can tell people what the numbers and figures in an article mean.
We call this data commentary.
And we'll look at three things.
Where to find the data, what it means, and moderating a claim.
Data commentary in journalism is important because tables and
figures are often difficult to understand.
A figure uses pictures like a chart or
a graph to show information while a table uses words and numbers.
If a reader just looks at the table or
figure, they might not understand the important information there.
Journalists use data commentary to help readers understand
these tables and figures.
At the beginning of the data commentary,
it's important to let the reader know which table or figure they're looking at.
We use the structure number of table or figure + verb.
The most common verb in data commentary is shows.
Other common verbs are presents, and illustrates.
So you can begin your data commentary by saying table 1 shows, or
figure 3 presents, or figure 2 illustrates.
You can use any of these verbs with both figures and tables.
Right after you tell the reader where to find the data,
you tell them what the data means.
You want to tell the reader something interesting about the data.
The structure of this is that + subject + verb + object.
Let's look at an example of these two things.
Here's some data in the form of a simple figure.
We'll call it figure 1.
Some people were asked which politician they like best.
A or B?
As you can see, politician A is more popular with the people than politician B,
so we begin our data commentary by telling the reader where the data is,
figure 1 shows, then we tell them what it means.
Figure 1 shows that our subject, people, our verb,
like, our object, politician A more than politician B.
Let's look at that again.
We tell them where it is, figure one shows, then we tell them what it means.
That people like politician A more than politician B.
The last part of data commentary, is moderating a claim.
Let's look at those two words.
A claim is when you say something is true.
A good example is the statement we just made.
People like politician A more than politician B.
We're saying that this is true.
To moderate a claim means you don't claim too much from the data.
What you say is reasonable.
You can't make a claim that is too strong.
At the moment, our claim is too strong.
Meaning that it is not totally true.
Let's use figure 1 as an example, and give you a little more data.
As you can see, the people are young people from the city of Chicago.
More of them preferred politician A to politician B, but
the difference is quite small, 53% to 47%.
The claim we made earlier was this,
figure 1 shows that people like politician A more than politician B.
We need to moderate this claim because it is too strong.
Do we have data from all people?
No, just young people, so we need to add that.
Do we have data from all cities?
No, only from Chicago, so we need to add that.
Was there a big difference in preference for A over B?
No, only a little difference, so we add that.
So now our claim is this, figure 1 shows that young people in
Chicago like politician A a little more than politician B.
Now we have motivated our claim, and it is an accurate commentary on the data.
So, in this video, we looked at data commentary.
We learned how to show the reader where the data is,
what it means, and how to moderate a claim.
You can test yourself by playing the data commentary game that follows this video.