The document discusses data commentary and provides guidance on its purpose, structure, and key elements. It explains that a data commentary presents results, interprets results, and discusses the significance and implications of results. It also provides tips on highlighting data, writing paragraphs, linking clauses, and qualifying claims.

1. ELT- 702 Academic Writing
 Data commentary
by, Betül GÜLERYÜZ
Osman AYDOĞAR
16.03.2012

2.  While data commentaries may be "stand-alone"
pieces of writing, they generally occur in the
Results or Discussion sections of a report or
thesis.
 The main purposes of a data commentary are to
present the results of research, interpret these
results, and to discuss the significance and
implications of the results.

3.  Data can often be best expressed by a chart,
graph, table, or other illustration.
 The type of writing that accompanies a visual
display is called data commentary.

4.  The data should be presented and analysed in logical manner;
in other words you are expected to analyse and evaluate the
data, not just describe it.

5. Why use a data commentary?
 Highlight results
 Assess standard theories, common beliefs, or
generals practices in light of the results
 Compare and evaluate different data sets
 Assess the reliability of data in terms of the methods
that produced it

6.  Discuss implications of the data
 Calls attention to something not directly apparent
 from the table, chart, or graph.
 Analyzes data for a reason: to support a claim which
 in turn helps achieve the main goal of the paper.

7. Structure of Data Commentary
 Data commentaries usually have the following
elements in the following order.
1. Location elements and/or summary statements
2. Highlighting statements
3. Discussions of implications, problems, exceptions,
recommendations, etc.

8. Paragraph structure of a data commentary:
 Topic sentence (claim)
 Location elements and summaries (support)
 Highlights (examples)
 Implications (restatement of claim)

10. Highlighting Statements
 The central sections of data commentaries consist of
highlighting statements.
 Highlighting statements are generalizations that you
can draw from the details of the data display.
 Highlighting statements need good judgment.
 They are an opportunity to show your intelligence..

11.  In particular, they are an opportunity for you to
demonstrate
 that you can spot trends or regularities in the data,
 that you can separate more important findings from
less important ones, and
 that you can make claims of appropriate strength

12. So, do not
 simply repeat all the details in words,
 attempt to cover all the information, or
 claim more than is reasonable or defensible.

13. Verbs for introducing highlights:
 Table 2 shows the most common factors are…
 Figure 2.3 illustrates the results of a study
 that…
 Table 9 demonstrates how the use of…
 …the most common are displayed in Table 3.
 …details of the operation are given in Figure
 4.4.
 …these qualities are suggested by Figure 9.3.
 Other verbs: provide, present, summarize, reveal,
indicate

14. Language Focus: Linking as-Clauses
 These linking clauses (where as does not equal since or
because) are exceptional in English grammar. In the
passive, these linking clauses have no subjects.
Compare the following sentences.
a. As it has been proved, the theory may have practical
importance.
b. As has been proved, the theory may have practical
importance.
 In sentence a there is a causal relationship between the
as-clause and the main clause. Because the theory has
been proved, it may have practical importance.

16. Some Specific ways for qualifying or moderating a
claim
 1-Probability

17. 2-Distance

19. 3-Generalization

22. 4-Weaker verbs

23. Indicative Summary
 - Indicates what has been done in the work.
 •Table 5 shows the most common modes of computer
infection for U.S. businesses.
 •Figure 4.2 gives the results of the second experiment.

24. Indicating the strengths of data results
 A reduced speed limit will result in fewer
accidents.
 A reduced speed limit may result in fewer accidents.
 A reduced speed limit could result in fewer
accidents.
 It is certain that…
 It is almost certain that…
 It is highly probable that…

25.  It is possible that…
 It is unlikely that…
 There is a strong possibility that…
 There is a slight possibility that…
 There is a remote possibility that…

26. Informative Summary
 - Provides a summary of the data.
 •Table 5 shows that home disks are the major source
of computer viruses.
 •Table 4.2 suggests that the experimental results
confirm the hypothesis.

27. Table 5. Means of PC Infection in U.S. Businesses
Source Percentage
 Disks from home  43%
 Electronic bulletin board  7%
 Sales demonstration disk  6%
 Repair or service disk  6%
 Company, client, or consultant disk  4%
 Other  9%
 Undetermined  29%

28.  1) A computer virus is a program that is specifically and
maliciously designed to attack a computer system, destroying
data. 2) As businesses have become increasingly dependent
on computer systems, concern over the potential
destructiveness of such viruses has also grown. 3) Table 5
shows the most common modes of infection for U.S.
businesses.-location and indicative summary
 4) As can be seen, in the majority of cases, the source of the
virus infection can be detected, with disks being brought to
the workplace from home being by far the most significant
(43%). 5) However, it is alarming to note that the source of
nearly 30% of viruses cannot be determined.-highlightment

29.  6) While it may be possible to eliminate home-to-
workplace infection by requiring computer users to run
antiviral software on diskettes brought from home,
businesses are still vulnerable to major data loss,
especially from unidentifiable sources of infection.
-implications

30. Combined qualifications
 A strong claim

31. We add some qualifications

32. We have a new claim:

33. Passive voice:
 a. The most common modes of infection are shown
in Table 5.
 b. Details of the fertilizers used are provided in
Table 2.
 c. The results of the second experiment are given in
Figure 4.2.

34. Passive Verbs in Reference to a Visual
 Shown in
 Illustrated in
 Presented in
 Given in
 Listed in
 Seen in
 Provided in
 Summarized in
 Seen from

35. Active voice:
 a. Table 5 shows the most common modes of
computer infections.
 b. Table 2 provides details of the fertilizer used.
 c. Figure 4.2 gives the results of the second
experiment

36. Active Verbs Following Reference to a Visual
 Shows *Presents
 Illustrates *Summarizes
 Demonstrates *Contains
 Provides *Depicts
 Lists
 Reports

37. In order to investigate the hypothesis that 8-year old boys
are more aggressive than 8-year old girls, 8-year old
children were observed playing in schoolyards and incidents
of certain aggressive behaviors were recorded.
Aggressive Girls Boys
behavior
Pushing 21% 35%
Kicking/Hitting 15% 61%
Cursing 9% 30%
Chasing 78% 1%

38. Commentary 1
 In order to investigate the hypothesis that 8-year old
boys are more aggressive than 8-year old girls, 8-year old
children were observed playing in schoolyards and
incidents of certain aggressive behaviors were recorded.
2)Table 1 shows that boys are more aggressive than girls.
3)The percentage of pushing is 21% of girl; on the other
hand that of boys is 35%. 4)Except for chasing, the
percentage of aggressive behavior is higher in boys.
5)From this data you can agree that boys are more
aggressive than girls. (Rating: 73)

39. Commentary 2
 In order to investigate the hypothesis that 8-year old
boys are more aggressive than 8-year old girls, 8-year old
children were observed playing in schoolyards and
incidents of certain aggressive behaviors were recorded.
2)As you can see in Table 1, we only considered four
human aggressive behaviors in our study. 3)The most
common children aggressive conduct are pushing,
kicking/hitting, cursing, and chasing. 4)After several
weeks of observation in different schools playground we
found the percentage that appeared on table 1. 5) (See
attachment 1) 6) Sixty percent (61%) of the boys like to
kick and hit compared to fifteen percent (15%) of the
girls. 7)This is more aggressive than chasing. 8)The
chasing behavior was the only one girls were more
aggressive than boys. (Rating: 77)

40. Commentary 3
 In order to investigate the hypothesis that 8-year old
boys are more aggressive than 8-year old girls, 8-year old
children were observed playing in schoolyards and
incidents of certain aggressive behaviors were recorded.
2)It was assumed that aggressive behavior consisted of
the following: i) pushing, ii) kicking and hitting, iii)
cursing, and iv) chasing. 3)As can be seen from the table
above, the average 8-year old boy was more aggressive
than the 8-year old girls. 4)Chasing was the one behavior
that was more pronounced for the girls. 5)This result,
however, does not disprove the theory since chasing
seems to be a less aggressive behavior than the other
behaviors that were tested. 6The 8-year old boys got
more involved with the more aggressive behavior, which
is kicking/hitting, much more than the 8-year old girls.
(Rating: 93)

41. Commentary 4
 In order to investigate the hypothesis that 8-year old boys are more
aggressive than 8-year old girls, 8-year old children were observed
playing in schoolyards and incidents of certain aggressive behaviors
were recorded. 2)At first glance it appears that 8-year old boys exhibit
more aggressive behavior than 8-year old girls if all four recorded
behaviors are equally weighed. 3)But, this last assertion is false.
4)Since the ability to record will vary with playground size and the
number of observers (not to mention the skills of the observers or
accounting for children entering or leaving the playground), and that it
takes a certain amount of an observer's time to note the behavior,
short-lived behaviors such as cursing or pushing could be under-
represented. 5)Simply because more can occur during the time an
observer notes another behavior. 6)Conversely, long-lived behaviors
such as chasing could be over-represented because they occur over a
longer period of time and thus allow more latitude for the observer
marking the behavior. (Rating: 93)