Following on from my post about writing a discussion, here are some tips on putting together a results section for your project/dissertation (in no particular order). These are the sorts of comments that I regularly find myself writing as feedback on drafts. Maybe next year I will remember to give this to all my students *first*…

1. Your results should focus on your* results*, not on the analysis methods. It is better/clearer to have a “statistical methods” section at the end of your methods, so you can focus your results section on telling the story of your data. In this section, you need to make sure that you justify each decision that you have made for the analysis (why did you pick that particular test? Why did you divide your data into categories in that particular way?)

2. You should always (at a minimum) include the test statistic, sample size (N) or degrees of freedom (d.f.), and p-value for every statistical test. Just reporting the p-value is not enough. If you are using different analytical techniques, follow the standard reporting for those techniques.

3. Report these outputs (and any other figures, like means or standard deviations) to 3 decimal places tops. You didn’t measure things to 9 decimal place accuracy, so don’t report with that level of accuracy either. If you measured body size to the nearest mm, you could report the mean body size to one decimal place, for example.

4. Always refer to your figures in the text, next to the analysis they are associated with. You can simply put the figure number in the parentheses after the stats, you don’t need a whole sentence that says “Figure 2 shows this relationship”. Each figure should have a clear legend that allows it to be understood without reference to the text. To stop stuff moving around when you get me to comment on it, paste your figures “in line with text” and write the legend underneath, not in a text box. You can pretty it up at the end before you submit. If you have multi-panel figures, label them a, b, c, d and refer to them as figure 1a, figure 1b rather than “top left” and “bottom right”.

5. You don’t need to explain in general what a particular test does, just why you used it: Say “To assess whether there were differences between categories, an ANOVA was used” rather than “ANOVAs test for differences between categories, so I used one to test whether…”

6. Ditto for figures. No need to explain that a scatter plot shows the data points. There might be an exception here if you have used a particularly complicated plotting technique.

7. Make sure you know the difference between *relationship*s (between two variables) and *differences *(in your response variable between categories)* *and which one you have tested for.

8. Tell me what the analysis you have just reported actually means. “There is a statistically significant difference” isn’t terribly informative. “Men are significantly taller than women” tells me a lot more. Always give the *direction of an effect* (was it a positive or negative relationship, was A larger or smaller than B?). Follow your statement with the results from the analysis.

9. If your results are not significant, use “non-significant”, not “insignificant” and avoid making any comment that suggests a relationship or a difference that isn’t supported by a your analysis (even a non-significant one). That’s why we do the analysis, to avoid drawing conclusions from eyeballing the data.

10. Look back at the statistics courses you have taken during your degree and get guidance as to how to present your results from there. Stick closely to the format. If you’re a Hull student, this can be found in the 2nd year Skills Stats Handbook (you all got one). Another source of inspiration is the results section of published papers that use similar analyses to yours.

11. Don’t worry about your results section seeming short. If you have correctly reported all the analyses that you should have carried out (i.e. done everything sensible, given your data), based on your hypotheses/aims/research questions, then your results might not be enormous, but so long as they are written correctly, that’s OK.

The tighter and better written your results section, the easier it is for the reader to follow. Key though, is that *you* understand what you have done, why you have done it and what it means. This needs to come through in your writing.