The results section is the heart of an empirical research report because it reveals the evidence that will be used to address the problem or question raised in the introduction. The content of the section would seem to be obvious: it is here that you present the data generated by your investigations. However, presenting data is by no means straightforward.

The main problem is to decide which data to present and how. Your investigations may have provided many pages of figures and hundreds of individual numbers (raw data) from dozens of analyses, which cannot all be included in a report, so your job is to organize and summarize. By way of example, let us consider the study on how the jazz chants teaching technique can improve vowel reduction (see Abstract). There, the researcher puts forward three hypotheses: (1) jazz chants would improve students’ pronunciation; (2) female students would improve more than male students; and (3) Catalan-dominant students would improve more than Spanish-dominant speakers. If the results section is to help prove or disprove these hypotheses, you must present the data in such a way that it provides insight into them.

One way to do this is to organize the section so that readers clearly see what findings were provided by the tests you described in the methods section. And, like the methods section, using subsections may be the most effective way of highlighting these findings. Our vowel reduction model opted for a four-part results section. The first subsection was entitled ‘Descriptive Statistics’ and provided information on gender, age, dominant first language and language-learning experience to show that the control and experimental groups were indeed comparable; and then, the model went on to have one subsection on each of the tests, called ‘Independent Samples T-Tests’, ‘Paired Samples T-Tests’ and ‘Correlations’, respectively.

Another way to decide which data to present is to reduce the amount of information to a manageable size by converting the raw data into means (averages). You can then display these means in the form of tables (graphics which organize information into columns and rows) and figures (graphics which organize information into charts, graphs, plots, drawings or any other illustration that is not a table). You can design these tables and figures to highlight changes over time, differences between the sexes, or – as in our vowel reduction model – differences between Catalan- and Spanish-dominant students. It is these observations, not the numbers and figures themselves, that are the response to your research questions. In the text, you will make generalizations about this data and point out significant changes, differences, trends and patterns that shed light on your main research questions. For the moment, merely indicate that they exist; do not interpret them, as that is the function of the discussion section. Also, make sure to inform your readers where they can find the information you are summarizing by giving an explicit reference to the table or figure in the text. For example, “This data shows that the control and experimental groups were similar in terms of the gender of the students (see Figure 4.1) and their dominant first language (see Figure 4.2)”.

Note that tables and figures have different functions. Tables are useful if you have numerous entries or precise numerical values, but they do not easily reveal general trends or relationships between variables. On the other hand, bar and line graphs are very good for highlighting trends and relationships but do not show precise numerical values and can only effectively display a limited number of variables. Note also that readers should be able to understand tables and figures on their own, without the support of the text.

Finally, and as the observations above suggest, some of the most important language you require in the results section is associated with tables and graphs. In particular, you need to be able to compare, contrast and describe trends.