From Hypotheses to Results

There is a natural balance between the hypotheses and the results sections, which provide a frame to the analysis. The following steps will make it sure that you set your hypotheses accurately, and that your results will either accept or reject those properly, instead of trying to “prove” anything.


Follow these six steps to set your hypotheses accurately:

  1. Structure them as follows: H1, H2, H3
  2. Name the variables in the order in which they occur or will be measured.
  3. Assign a relationship among the variables and reference the population.
  4. Stick to what will be studied, not implications or your value judgments.
  5. Make them as specific and succinct as possible.
  6. Avoid words or terms that do not add to their meaning; words significant or significance; the word “prove”; using two different terms to refer to the same variable.


The analysis systematically carries out that you planned to do in your Research Design and Methodology chapter. Hence, the things to do are:

  • Applying the chosen variables
  • Applying the chosen method(s) to the dataset
  • Qualitative or quantitative analysis
  • Analysis or data interpretation?
  • Structuring the analysis along the hypotheses or methodological milestones
  • Being consise, transparent and objective


Your results simply answer to your research questions or hypotheses. They are summing up briefly the findings of the analysis.

To do list:

  • Structuring the results in line with the hypotheses e.g. H1, H2, H3
  • The results of a study do not prove anything but accept or reject, confirm or disconfirm the hypotheses
  • The page length of this section is set by the amount and types of data to be reported
  • Being factual and concise,
  • Using non-textual elements appropriately to present results in a more effective manner, such as figures and tables, if necessary

To avoid list:

  • Discussing or interpreting your results widely
  • Reporting background information or attempting to explain your findings
  • Ignoring negative results
  • Including raw data or intermediate calculations
  • Presenting the same data or repeating the same information more than once
  • Providing data that is not critical to answering the research question
  • Confusing figures and tables

Photo retrieved (25/04/2018):

Editor A. S., 2018