Do not blindly follow the data you have collected; make sure your original research objectives inform which data does and does not make it into your analysis. All data presented should be relevant and appropriate to your aims. Irrelevant data will indicate a lack of focus and incoherence of thought. In other words, it is important that you show the same level of scrutiny when it comes to the data you include as you did in the literature review. By telling the reader the academic reasoning behind your data selection and analysis, you show that you are able to think critically and get to the core of an issue. This lies at the very heart of higher academia.
It is important that you use methods appropriate both to the type of data collected and the aims of your research. You should explain and justify these methods with the same rigour with which your collection methods were justified. Remember that you always have to show the reader that you didn’t choose your method haphazardly, rather arrived at it as the best choice based on prolonged research and critical reasoning. The overarching aim is to identify significant patterns and trends in the data and display these findings meaningfully.
3. Quantitative work
Quantitative data, which is typical of scientific and technical research, and to some extent sociological and other disciplines, requires rigorous statistical analysis. By collecting and analysing quantitative data, you will be able to draw conclusions that can be generalised beyond the sample (assuming that it is representative – which is one of the basic checks to carry out in your analysis) to a wider population. In social sciences, this approach is sometimes referred to as the “scientific method,” as it has its roots in the natural sciences.
4. Qualitative work
Qualitative data is generally, but not always, non-numerical and sometimes referred to as ‘soft’. However, that doesn’t mean that it requires less analytical acuity – you still need to carry out thorough analysis of the data collected (e.g. through thematic coding or discourse analysis). This can be a time consuming endeavour, as analysing qualitative data is an iterative process, sometimes even requiring the application hermeneutics. It is important to note that the aim of research utilising a qualitative approach is not to generate statistically representative or valid findings, but to uncover deeper, transferable knowledge.
The data never just ‘speaks for itself’. Believing it does is a particularly common mistake in qualitative studies, where students often present a selection of quotes and believe this to be sufficient – it is not. Rather, you should thoroughly analyse all data which you intend to use to support or refute academic positions, demonstrating in all areas a complete engagement and critical perspective, especially with regard to potential biases and sources of error. It is important that you acknowledge the limitations as well as the strengths of your data, as this shows academic credibility.
6. Presentational devices
It can be difficult to represent large volumes of data in intelligible ways. In order to address this problem, consider all possible means of presenting what you have collected. Charts, graphs, diagrams, quotes and formulae all provide unique advantages in certain situations. Tables are another excellent way of presenting data, whether qualitative or quantitative, in a succinct manner. The key thing to keep in mind is that you should always keep your reader in mind when you present your data – not yourself. While a particular layout may be clear to you, ask yourself whether it will be equally clear to someone who is less familiar with your research. Quite often the answer will be “no,” at least for your first draft, and you may need to rethink your presentation.
You may find your data analysis chapter becoming cluttered, yet feel yourself unwilling to cut down too heavily the data which you have spent such a long time collecting. If data is relevant but hard to organise within the text, you might want to move it to an appendix. Data sheets, sample questionnaires and transcripts of interviews and focus groups should be placed in the appendix. Only the most relevant snippets of information, whether that be statistical analyses or quotes from an interviewee, should be used in the dissertation itself.
In discussing your data, you will need to demonstrate a capacity to identify trends, patterns and themes within the data. Consider various theoretical interpretations and balance the pros and cons of these different perspectives. Discuss anomalies as well consistencies, assessing the significance and impact of each. If you are using interviews, make sure to include representative quotes to in your discussion.
What are the essential points that emerge after the analysis of your data? These findings should be clearly stated, their assertions supported with tightly argued reasoning and empirical backing.
10. Relation with literature
Towards the end of your data analysis, it is advisable to begin comparing your data with that published by other academics, considering points of agreement and difference. Are your findings consistent with expectations, or do they make up a controversial or marginal position? Discuss reasons as well as implications. At this stage it is important to remember what, exactly, you said in your literature review. What were the key themes you identified? What were the gaps? How does this relate to your own findings? If you aren’t able to link your findings to your literature review, something is wrong – your data should always fit with your research question(s), and your question(s) should stem from the literature. It is very important that you show this link clearly and explicitly.
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When writing a dissertation or thesis, the results and discussion sections can be both the most interesting as well as the most challenging sections to write.
You may choose to write these sections separately, or combine them into a single chapter, depending on your university’s guidelines and your own preferences.
There are advantages to both approaches.
Writing the results and discussion as separate sections allows you to focus first on what results you obtained and set out clearly what happened in your experiments and/or investigations without worrying about their implications.
This can focus your mind on what the results actually show and help you to sort them in your head.
However, many people find it easier to combine the results with their implications as the two are closely connected.
Check your university’s requirements carefully before combining the results and discussions sections as some specify that they must be kept separate.
The Results section should set out your key experimental results, including any statistical analysis and whether or not the results of these are significant.
You should cover any literature supporting your interpretation of significance. It does not have to include everything you did, particularly for a doctorate dissertation. However, for an undergraduate or master's thesis, you will probably find that you need to include most of your work.
You should write your results section in the past tense: you are describing what you have done in the past.
Every result included MUST have a method set out in the methods section. Check back to make sure that you have included all the relevant methods.
Conversely, every method should also have some results given so, if you choose to exclude certain experiments from the results, make sure that you remove mention of the method as well.
If you are unsure whether to include certain results, go back to your research questions and decide whether the results are relevant to them. It doesn’t matter whether they are supportive or not, it’s about relevance. If they are relevant, you should include them.
Having decided what to include, next decide what order to use. You could choose chronological, which should follow the methods, or in order from most to least important in the answering of your research questions, or by research question and/or hypothesis.
You also need to consider how best to present your results: tables, figures, graphs, or text. Try to use a variety of different methods of presentation, and consider your reader: 20 pages of dense tables are hard to understand, as are five pages of graphs, but a single table and well-chosen graph that illustrate your overall findings will make things much clearer.
Make sure that each table and figure has a number and a title. Number tables and figures in separate lists, but consecutively by the order in which you mention them in the text. If you have more than about two or three, it’s often helpful to provide lists of tables and figures alongside the table of contents at the start of your dissertation.
Summarise your results in the text, drawing on the figures and tables to illustrate your points.
The text and figures should be complementary, not repeat the same information. You should refer to every table or figure in the text. Any that you don’t feel the need to refer to can safely be moved to an appendix, or even removed.
Make sure that you including information about the size and direction of any changes, including percentage change if appropriate. Statistical tests should include details of p values or confidence intervals and limits.
While you don’t need to include all your primary evidence in this section, you should as a matter of good practice make it available in an appendix, to which you should refer at the relevant point.
Details of all the interview participants can be found in Appendix A, with transcripts of each interview in Appendix B.
You will, almost inevitably, find that you need to include some slight discussion of your results during this section. This discussion should evaluate the quality of the results and their reliability, but not stray too far into discussion of how far your results support your hypothesis and/or answer your research questions, as that is for the discussion section.
See our pages: Analysing Qualitative Data and Simple Statistical Analysis for more information on analysing your results.
This section has four purposes, it should:
- Interpret and explain your results
- Answer your research question
- Justify your approach
- Critically evaluate your study
The discussion section therefore needs to review your findings in the context of the literature and the existing knowledge about the subject.
You also need to demonstrate that you understand the limitations of your research and the implications of your findings for policy and practice. This section should be written in the present tense.
The Discussion section needs to follow from your results and relate back to your literature review. Make sure that everything you discuss is covered in the results section.
Some universities require a separate section on recommendations for policy and practice and/or for future research, while others allow you to include this in your discussion, so check the guidelines carefully.
Starting the Task
Most people are likely to write this section best by preparing an outline, setting out the broad thrust of the argument, and how your results support it.
You may find techniques like mind mapping are helpful in making a first outline; check out our page: Creative Thinking for some ideas about how to think through your ideas. You should start by referring back to your research questions, discuss your results, then set them into the context of the literature, and then into broader theory.
This is likely to be one of the longest sections of your dissertation, and it’s a good idea to break it down into chunks with sub-headings to help your reader to navigate through the detail.
Fleshing Out the Detail
Once you have your outline in front of you, you can start to map out how your results fit into the outline.
This will help you to see whether your results are over-focused in one area, which is why writing up your research as you go along can be a helpful process. For each theme or area, you should discuss how the results help to answer your research question, and whether the results are consistent with your expectations and the literature.
The Importance of Understanding Differences
If your results are controversial and/or unexpected, you should set them fully in context and explain why you think that you obtained them.
Your explanations may include issues such as a non-representative sample for convenience purposes, a response rate skewed towards those with a particular experience, or your own involvement as a participant for sociological research.
You do not need to be apologetic about these, because you made a choice about them, which you should have justified in the methodology section. However, you do need to evaluate your own results against others’ findings, especially if they are different. A full understanding of the limitations of your research is part of a good discussion section.
At this stage, you may want to revisit your literature review, unless you submitted it as a separate submission earlier, and revise it to draw out those studies which have proven more relevant.
Conclude by summarising the implications of your findings in brief, and explain why they are important for researchers and in practice, and provide some suggestions for further work.
You may also wish to make some recommendations for practice. As before, this may be a separate section, or included in your discussion.
The results and discussion, including conclusion and recommendations, are probably the most substantial sections of your dissertation. Once completed, you can begin to relax slightly: you are on to the last stages of writing!