Style Writing and structuring reports

198 Chapter 8 n Presenting your project in written form Figure 8.3 Bar chart showing degree classification of 100 students and should be included as close to their original reference point as possible, but not before. Take, as an example, Table 8.1. This table presents the final degree classifications of 100 students who completed their Computer Science course in 2009. Table 8.1 presents these data in a much clearer way than you could hope to achieve using text alone. For example, compare this table with: ‘Seven students obtained first class degrees, twenty three obtained an upper second, thirty eight achieved a lower second, seventeen received third class degrees, ten achieved only a pass degree, and five students failed’. 1st 2:1

2:2 3rd

Pass Fail 7 23 38 17 10 5 Table 8.1 Degree classification of 100 students Although Table 8.1 is easier to follow than the text presented above, it is not necessarily the best way of presenting these data. Figure 8.3 is perhaps a clearer way of interpreting these results and it provides a more ‘holistic’ view of the spread, pattern, or distribution of degree grades. Note that the distribution of data is only relevant when the data are of at least ordinal scaling. In other words, the categories into which the data are arranged represent an increasing magnitude of one kind of another for example, the position of runners in a race; good, average or poor software quality and so on. Data that merely represent classes in which the order is irrelevant for example, gender or religious belief have no distribution as such and the order of the columns in these charts is unimportant. In this case the chart can only emphasise the difference between the number of items identified within each category. Figure 8.3 is a vertical bar chart or column chart. These charts can also be presented horizontally, but generally the vertical representation is preferred. Bar charts are used to present categorical data and are useful for presenting the results of questionnaires which have used Likert-type scales. These scales ‘indicate strength of agreement or disagreement with a given statement’ Bell 2005: 219. For example, ‘Do you think this software is poor, average, or good?’ Note how, on this chart, the data have been split into columns with gaps between, both axes have been labelled and the chart has been uniquely titled as Figure 8.3 with a corresponding brief label. 8.4 Data presentation 199 Figure 8.4 Histogram showing age of 100 students on graduation For continuous data an alternative to the bar chart is required as the data are not arranged in distinct categories but can take any real value for example, age, size, weight, etc.. In these cases, a histogram is used. Histograms present data in a similar way to bar charts in that columns are used to represent frequencies of occurrence of a particular data item. However, because histograms present continuous data, it is now up to you how you split the data into unique categories. Remember that bar charts have their categories defined for them based on the categories defined within the data they represent. As an example, Figure 8.4 presents a histogram showing the age of the 100 Computer Science students at graduation. In Figure 8.4 the age of graduates has been split into ten unique categories; 18 to 20, 20 to 22, 22 to 24, 24 to 26 years old and so on. It has been assumed, in this case, that each category’s upper boundary is actually one day before the year indicated, so that peo- ple whose even-numbered birthday 20, 22, 24, etc. falls on the day of the survey will be placed in the next category up i.e., 20 to 22 actually represents 20 years to 21 years 364 days old. Each column now represents the number of students that fall within the defined range. Notice how the bars in this chart are now touching. This highlights the fact that the data are continuous and there is no absolute break between the categories. There is no reason why you could not, alternatively, have defined the categories as; 20 to 25, 25 to 30, 30 to 35, etc. This results in the histogram shown in Figure 8.5. Figure 8.5 Histogram showing age of 100 students on graduation