Results and Discussions

The Results and Discussion sections are the “meat” of most engineering reports. The role that they play in a lab report is obvious; in other types of reports, they can fulfill different purposes. In a design report, the results and discussion may involve an evaluation of the design or method used. In a feasibility or case study, the results and discussion section would involve measuring the feasibility or evaluating the success of one or more solutions. Not all reports, however, will include these components – proposals, for example, will likely not have any results to discuss, since it looks forward to action to be done in the future. A final report, however, might discuss whether or not the project lived up to the objectives, budget and timeline laid out in the proposal.

1. Together or Separate: In writing these components of your report, you are faced with one major decision with significant implications: i) combine the results and the discussion sections, or ii) keep them separate? Both require attention to the organization and division into topics and subtopics.

i. Combining the results and discussion section allows for more coherence, because it allows you to discuss results of a particular test or method immediately after presenting them. However, if you decide to forego the distinction between results and discussion, you will need to divide your section into appropriate subsections, potentially into different topics or tests: for example,

3.1 Composition of Samples A – D from SEM analysis
3.2 Strength of Samples A – D
3.3 Flexibility of Samples A – D

ii. Keeping results and discussion separate, on the other hand, allows you to discuss all of the results at one time. In the above example, it may be more important to discuss the relationships between composition, strength and flexibility of individual samples than it is to compare the features of all four samples. In this case, you may want to hold off on discussing the results until you have presented all of them. The headings for the discussion section, then, may look like this example:

4.1 Relationship between Composition, Strength and Flexibility in Sample A
4.2 Relationship between Composition, Strength and Flexibility in Sample B . . .

2. Presenting Results: involves using a combination of visual aids and prose. Whenever possible, use visual aids such as tables, charts, or graphs to represent results in an easy to read and understand format (See also Components of Reports / Using Visuals in Reports). When using visuals to present results, however, be sure that you do the following:

  1. Label and title all graphs, charts, and visuals clearly and precisely (Table 1.1: Composition and Strength of Samples A – D)
  2. Introduce the results and visuals in the body of the report (Table 1.1 (below) presents the composition and strength of the samples as determined by the SEM).
  3. Use sentences to highlight the key result (As seen in Table 1.1, Sample A showed the highest carbon content, and was also the strongest)

In-text or Appendices? In presenting results, you also need to be selective: some material may be more suited to an appendix than the body of the report itself. When making the decision to include results in the body of the paper or to place them in the appendix, you should ask yourself whether or not the information is pivotal to the discussion and understanding of the conclusions of the report. In the above example, the calculations used to determine strength and flexibility numbers may not play a significant role in the discussion; in that case, they can be placed in the appendix, with possibly one sample calculation placed in the body of the report. If you do include appendices in your report, be sure to refer to them in the body of the report: for example, “(See Appendix 3.1.1 for derivation of strength numbers for samples B-D.)”

3. Conducting Discussion: There are two key elements to discussion: analysis and interpretation. The difference between these two elements is subtle, but both aspects are essential for a complete understanding of the material (See also Types of Documents / Lab Report for genre specific instruction on results / discussion and particularly (on page 3, questions you might ask to fill out your discussion section).

Both analysis and interpretation involve drawing conclusions from the data presented in results. In doing either, be sure to clearly link your claims to specific sets of data, and logically explain how the data supports your claim.

Analysis involves explaining the results and identifying the conclusions you can draw from them. This can involve highlight key results and placing them in the context of other results, as in the below example.

The results for Sample A are as expected, given its composition (75% poly para-phenylenetere-phthalamide, as seen in Figure 3.1. As shown in Tables 3.2 and 3.3, Sample A was both the strongest and most flexible material. These features are typical of a composite with a high level of poly para-phenyleneterephthalamide content [1].

In the above example, the claim is that the results for Sample A are expected, given its composition. The data that supports that claim (from Figure 3.1) is that Sample A is the strongest and most flexible material, and that Sample A is made up of 75% poly para-phenyleneterephthalamide. The logical explanation is that this composite material is known to be flexible and strong (from source [1]).

Interpretation involves explaining the significance of these conclusions, identifying the potential limitations of the experimental method and their effect on the results, and accounting for any potential errors. The below example identifies what the results and the conclusions drawn from them might mean in a wider context:

Of the four samples, Sample A is best suited for use in protective clothing applications. Its high strength allows it to provide sufficient protection while its malleability allows it to be shaped to the contours of the human body.

This second example, below, identifies a potential limitation of the method, and how they might cast the above conclusion into doubt. Finally, it proposes future work that might help remove this limitation.

However, the way that we evaluated flexibility -measuring the amount of rotational stress before breakage – may not accurately reflect the manufacturing process for the protective clothing or usage patterns. Accounting for this application would involve measuring more and different types of stresses and their impact on the material.

Reporting potential sources of error is an important part of labs and research projects. However, students often include a list of possible errors without a sense of a) their potential impact on the results b) the likelihood that they played a role in the results, and c) how to avoid them in future studies, as in the below example:

Some potential sources of error are: human error, precision of measurements, testing the same sample for strength and flexibility, etc.

A better account of potential sources of error in this experiment might state the following:

Errors in the measurement of material flexibility may have resulted from our testing method. In all but one case, we tested strength and flexibility on the same sample of the materials. Both tests involved applying stress to the samples. Our measures of flexibility in samples B, C, and D may be lower than actual because of the stress applied to sample beforehand. We were able to obtain two pieces of samples A, and tested strength on one and flexibility on the other. While the effect of testing both properties on one sample is unknown, it is likely that applying strength testing may have reduced the flexibility of the material or made breakage more likely. Unfortunately, we only had access to one sample of B-D.