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For most readers, the results is the most tedious and boring part; it’s hard to make a bunch of sentences filled with numbers easy to read. However, obviously, this is an essential part of the paper and must be done well. You can help the reader by organizing the results into sections (if you have enough to justify it, obviously), breaking up the sentence structure such that not every sentence reads the same way, and using figures and tables judiciously. Don’t, however, over-use figures and tables; a bar graph figure that presents two means, for instance, isn’t usually necessary; the reader knows what those two means are (you presented them in the body of the results section) and you don’t need a figure to make that comparison again. On the other hand, comparing multiple means and presenting interactions graphically is very helpful to the reader. Again, refer to existing articles for examples!

Follow APA style* on how to present test statistics, p values, and descriptive statistics (means, SDs, etc). Also. follow APA style for figures and tables.

Avoid making any interpretations of the data in this section (save that for the Discussion). This section merely presents the data and the statistical comparisons you performed on it.

Discussion

The goal of a Discussion is to explain and interpret your data in the context of the existing literature. Therefore, you will HAVE to revisit the literature, no matter what, in order to write a good Discussion.

If your data supported your hypothesis, you need to write about existing published studies so the reader can see why it is that your data are consistent with and expand upon/add to what is already known. You will undoubtedly say some of the things you said in the

If your data do not support it (remember: that’s okay! Science is designed to test hypotheses, not “prove” hypotheses), you will have a lot to say about why. There are three possibilities:

1. Your hypothesis was wrong. THIS SHOULD BE WHERE YOU BEGIN. You need to find literature that helps you present a reasonable explanation for the fact that, even though you had a reasonable hypothesis (which you showed you did, in the Intro), you might have been wrong. This is tricky; you don’t want to negate your whole Intro by painting a picture that makes you look foolish for making the prediction you made. So, you need to navigate these waters carefully, making it clear that despite the good reasons you had for your hypothesis, there might be weaknesses in that argument. To do this, you need to find additional literature. For instance, there might be a study that found something like you found, but in an experiment that was not directed at exactly the same issue as your experiment.

There are sometimes trends in your data that you can refer to as promising. Maybe your hypothesis wasn’t supported statistically but the p value was .09 and the means were in the predicted direction. In this case, you probably want to be more optimistic that your hypothesis was indeed correct, and you can lead easily into the methodological problems (below) that might have caused you problems. But be really careful when you talk about trends; if your alpha was set at .05, you have to stick to that. You can’t suddenly act like everything is okay because you were close to .05.

2. Your hypothesis was right but you didn’t have the right method to test it. Here you can go over the various aspects of your procedure that might have reduced the likelihood of finding a significant effect (that is, the method reduced the power of your experiment).

3. Your hypothesis was right and the method was okay, but you didn’t have enough power because of small sample size. If you anticipated the effect size to be small (that is, you didn’t expect there to be HUGE differences between conditions), a small sample will not be adequate to find that relatively small effect.

Students sometimes focus entirely on #2 and 3, and as a result the Discussion does not do its job of discussing #1. Do NOT do that! You must give primary attention to explaining why the hypothesis may have been incorrect (#1). Plus, if you focus entirely on 2 and 3, your Discussion will be devoid of references, and you will have failed at the job of keeping your data in the context of the existing literature. In other words, methodological limitations can be mentioned in the Discussion, but should not be the focus.

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