Constructing tables

The clarity of tables can be improved by paying attention to their size, complexity and organisation, as well as to the captions and the prose descriptions of the tables that appear in the appropriate parts of the text.

Table 3.5.1 The percentage of articles containing tables and graphs in four different journals in 2005

Journal

No. of

% containing % containing % containing

(2005)

articles

tables

figures

both

J. Educational Psychology

56

96

70

61

American Psychologist

43

47

47

35

Studies in Higher Education

40

55

23

8

J. Scholarly Communication

20

10

0

0

Large tables and figures are comparatively rare in most research articles. Nonetheless, in the 2005 volume of the Journal of Educational Psychology, some twenty per cent of the tables occupy whole pages (approximately A4 size). This might be acceptable in an Appendix, but it makes life difficult for readers when such large tables are presented in the body of the text. Furthermore, another ten per cent or so of the tables in this same journal were printed sideways in either the right- or the left-hand column of the two-column page. Readers thus have to reorient the page in order to follow these whilst trying to read the text. As most research articles are available on-screen these days, it is worth thinking more about how to present information in screen-size tables that do not require head/page turning.

The complexity of tables can be reduced by paying attention to some simple rules. Such rules are:

1 split large tables into smaller ones;

2 produce one overall summary table rather than several small tables; for example, Table 2.1.1 (p. 26) summarises the data shown in four tables in the original article;

3 provide clear captions that say what the table is about, or tell the reader what the table shows (some people look at the tables first before reading the text);

4 round off the numbers so that readers can make meaningful comparisons more easily (giving data to four or five decimal points gives a misleading measure of accuracy);

5 consider including averages (averages not only summarise the data but they also allow the reader to grasp better the spread of the scores presented); and

6 use the same layout for a series of tables to avoid subsequent confusion for the reader.

Tables 3.5.2 and 3.5.3 show the effects of rounding. The underlying organisation of a table needs careful thought. The reader needs to be able to grasp this intuitively, or at least quickly, so that data can be retrieved and inferences can be made correctly. Table 3.5.4 shows an original layout that is clarified in Table 3.5.5.

Table 3.5.5 is more successful, because its organisation matches how reading across the table fits in with the language one would use to describe the contents in the text. It is easier to read the productivity scores from left to right in Table 3.5.5, following the labels 'enthusiastic doers' and 'enthusiastic thinkers', than it is following the labels 'thinkers enthusiastic' and 'thinkers anxious' in Table 3.5.4. In addition, higher numbers are placed at the top of Table 3.5.5 rather than at the bottom.

Table 3.5.2

An

original table that contravenes ru

le 2 by giving data too

accurately*

Number of applicants (thousands)

1997 2000

2003

2006

Men

159.61 350.73

395.35

399.41

Women

100.31 152.46

220.27

310.64

Total

259.92 503.19

615.62

710.05

* Fictitious data.

Table 3.5.3

The data in Table 3.5.2, rounded up*

Number of applicants (thousands)

1997 2000

2003

2006

Men

160 351

395

399

Women

100 152

220

311

Total

260 503

615

* Fictitious data.

Table 3.5.4 The average productivity scores of different kinds of writers*

Enthusiastic Anxious

Table 3.5.4 The average productivity scores of different kinds of writers*

Enthusiastic Anxious

Thinkers

20.9

18.1

(N)

(15)

(12)

Doers

32.6

19.8

(N)

(19)

(4)

* Fictitious data.

Table 3.5.5 The data

in Table 3.5.4,

reorganised to make it easier to read*

Doers

Thinkers

Enthusiastic

32.6

20.9

(N)

(19)

(15)

Anxious

19.8

18.1

(N)

(4)

(12)

* Fictitious data.

* Fictitious data.

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