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EXPLORATORY DATA ANALYSIS: FREQUENCIES, PERCENTAGES AND CROSS-TABULATIONS 511<br />

Box 24.7<br />

Representing combined categories of rating scales<br />

Satisfaction with course<br />

Low (1–3) High (4–7) Total<br />

Male 60 85 145<br />

(41.4 %) (58.6 %) (100 %)<br />

Female 35 45 80<br />

(43.7 %) (56.3 %) (100 %)<br />

Total 95 130 225<br />

(42.6 %) (57.4 %) (100 %)<br />

Difference −2.1% +1.9%<br />

(medium and high) then a different story could be<br />

told (Box 24.7).<br />

By lo<strong>ok</strong>ing at the percentages, here it appears<br />

that there is not much difference between the<br />

males and the females, and that both males and<br />

females are highly satisfied with the course. At<br />

issue here is the notion of combining categories, or<br />

collapsing tables, and we advocate great caution<br />

in doing this. Sometimes it can provide greater<br />

clarity, and sometimes it can distort the picture.<br />

In the example it is wiser to keep with the<br />

original table rather than collapsing it into fewer<br />

categories.<br />

In examining data we can lo<strong>ok</strong> to see how evenly<br />

or widely the data are distributed. For example, a<br />

line graph shows how respondents voted on how<br />

well learners are guided and supported in their<br />

learning, awarding marks out of ten for the voting,<br />

with a sample size of 400 respondents (Box 24.8).<br />

One can see here that the data are skewed, with<br />

more votes being received at the top end of the<br />

scale. There is a long tail going to the negative end<br />

of the scores, so, even though the highest scores<br />

are given at the top end of the scale, we say that<br />

this table has a negative skew because there is a<br />

long tail down.<br />

By contrast, let us lo<strong>ok</strong> at a graph of how much<br />

staff take on voluntarily roles in the school, with<br />

150 votes received and awarding marks out of 10<br />

(Box 24.9).<br />

Here one can observe a long tail going toward<br />

the upper end of the scores, and the bulk of the<br />

scores being in the lower range. Even though most<br />

of the scores are in the lower range, because the<br />

long tail is towards the upper end of the scale this<br />

is termed a positive skew. The skewness of the data<br />

is an important feature to observe in data, and to<br />

which to draw attention.<br />

Chapter 24<br />

Box 24.8<br />

How well learners are cared for, guided and<br />

supported<br />

Box 24.9<br />

Staff voluntarily taking on coordination roles<br />

500<br />

200<br />

400<br />

Count<br />

300<br />

200<br />

Count<br />

100<br />

100<br />

0<br />

1<br />

2<br />

3<br />

4<br />

5<br />

6<br />

7<br />

8<br />

9<br />

10<br />

0<br />

1<br />

2<br />

3<br />

4<br />

5<br />

6<br />

7<br />

8<br />

9<br />

10

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