What the Results are supposed to do
The purpose of the results section is to answer the research questions by identifying patterns in the data. So the results text should highlight relevant patterns. The Results section should not rehash every data point: that’s what the figure and tables are for.
The role of figures and tables
In quantitative research, figures and tables can be used to present data points and summarise data. They should present the data so that the reader can easily draw their own conclusions about it.
What the Results text should describe
Let’s say your research question is:
How does the breaking strength of tree branches differ across three species?
And you have the following results:
Table 1: Branch breaking strength for three tree species.
| Species | Strength (maximum force, N) |
|---|---|
| A | 20 |
| B | 40 |
| C | 60 |
Then you might be tempted to describe the results like this:
Table 1 shows the breaking strength for three tree species. Our results show that species A had a strength of 20 N, species B a strength of 40 N, and species C a strength of 60 N.
This only restates the table. It doesn’t say what the differences mean for the research question, and it doesn’t point out a relevant pattern. But the purpose of the Results is to answer the research question by identifying patterns in the data. So what to write instead?
Let’s look at the research question again:
How does the breaking strength of tree branches differ across three species?
This question looks like its easy to answer: the table already shows how the species differ. But when you’re deep in the data, it’s hard to think beyond the numbers. So take a step back and zoom out. Why are we looking at these specific species? What do they represent? And what is the bigger question this research is trying to address?
In this fictional example, say we’re studying tree strength because we want to know which trees to plant in a city with regular strong winds. Now consider what the species represent. From a practical point of view, we might care about how much shade they offer in crowded cities or how much water they need to survive. From a scientific point of view, we might ask whether strength relates to where the species evolved, for example in windier regions.
In other words, we need to think about what kinds of patterns we’re interested in, why we’re comparing these species, and what we’re trying to achieve. Then the data start to have meaning beyond the data points themselves. Our new results could become, for example:
Table 1: Branch breaking strength and traits of three tree species.
| Species | Canopy size | Water needs | Strength (maximum force, N) |
|---|---|---|---|
| A | Medium | Low | 20 |
| B | Big | Medium | 40 |
| C | Small | High | 60 |
Species C had the highest breaking strength (60 N), even though it has the smallest canopy and the highest water needs (Table 1).
Notice that this sentence stays with the data, yet also answers the research question by identifying a pattern (“highest breaking strength”).
Do canopy size and water needs belong in the Results section?
Perhaps, perhaps not. It’s a matter of preference, and conventions differ by field and journal. I chose to include them in this example, otherwise my example became too thin ;)
Describing the results means interpreting the data
While describing results appears to be a factual task, the Results section is already somewhat subjective. Once you’ve chosen what to compare, the numbers themselves are factual. But you, as the researcher, decide which comparisons and findings get the most attention and are used to answer your research questions.
But doesn't interpretation belong in the Discussion?
Yes and no. In my opinion, the Results should interpret the data. The Discussion should interpret the findings. In the example above, noting that species C was the strongest despite its small canopy interprets the data. Saying what that means for planting trees in a windy city interprets the findings. See also: Results vs. Discussion
In short: how to describe findings
- State the pattern that answers the research question, not every value.
- Give only the numbers the pattern depends on, and refer to the table or figure for the rest.
- Save what the pattern means for the Discussion.
The same goes for graphs: don’t describe every point, say what the graph shows.