My friend, I swear I followed every single step she said and in the end what I had was so far from it that I was even embarrassed to call it a lasagna. INSIGHT: The logic of a recipe is that if you follow every single step, you should be able to reproduce it exactly every time and make great meals. Because it is irrelevant that you had an incredible research question or aim.
You will have findings, but they will have very little validity.
You go to the doctor because you are feeling weak and without energy (the research problem). Because taking an X-ray of a foot will not tell you the causes and symptoms of a weakness. Oh, just one more thing (I promise): I am not here to try to explain to you what your methodology should be.
Therefore, no matter what subject area you're working in, your methodology section will include the following: While the outline of your methodology section will look much the same regardless of your discipline, the details are liable to be quite different depending on the subject area in which you're studying.
Let's take a look at some of the most common types of dissertation, and the information required in a methodology section for each of them.
A scientific study The methodology section for a scientific study needs to emphasise rigour and reproducibility above all else.
Your methods must appear robust to the reader, with no obvious flaws in the design or execution.
Remember that a scholar might use any single part of your methodology as a departure point for their own work; they might follow your experiment design but choose a different model for analysing the results, or vice versa!
A study in the social or behavioural sciences As with a scientific study, a social or behavioural sciences methodology needs to demonstrate both rigour and reproducibility, allowing another researcher to reproduce your study in whole or in part for their own ends.
You should not only include the necessary information about your equipment, lab setup, and procedure to allow another researcher to reproduce your method; you should also demonstrate that you've factored any variables that are likely to distort your data (for example, by introducing false positives into your design), and that you have a plan to handle these either in collecting, analysing, or drawing conclusions from your data.
Your methodology should also include details of – and justifications for – the statistical models you'll use to analyse your data.