Reading time: 3 minutes - The Results Section of a Lab Report needs to be crisp, clear, concise.

Here we talk about how to avoid these issues to get closer to the perfect Results Section.

Error 1/3

The Error: Wrong Structure

There is a widely agreed structure for Lab Report Results Sections, which goes like this:

First, introduce your data and whether you did any calculations or data cleaning to end up with the data you’ve got.

For example:

“The data here is the happiness score for participants that either drank 2 litres of hot chocolate or 2 litres of chocolate milk. Happiness score was calculated by taking the mean of the totals of three happiness questionnaires.”

Second, you offer your descriptive statistics. This is most often the means and standard deviations of the results in your study. You would most often have the descriptive statistics in a beautifully formatted table.

For example:

“The descriptive statistics for the study can be found in Table 1.”

Third, you have your inferential statistics. This is the output from your statistical tests. Your statistical tests can figure something out from your data. In other words, it can infer something, which is why they are inferential. Let’s imagine we did a paired samples t-test on our happiness data.

For example:

A paired samples t-test found a statistically significant difference between happiness scores for those that drank 2 litres of hot chocolate compared to those who drank 2 litres of chocolate milk (t=7.459, df=7, p<.001).

Students will very often get this structure incorrect, usually in two ways:

Firstly, students forget to have the introductory section to the data, which is actually pretty crucial. Your reader may not know exactly what kind of detail you’re looking at.

Secondly, students will put the descriptive statistics after the inferential statistics. This is quite peculiar given that they’ve already analysed the data and told us the insights gained from statistical analysis.

Getting the structure correct is so easy to do, and getting it wrong is such a simple mistake but will lose you many marks. Make sure you don’t make this simple but quite significant mistake.

Error 2/3

The Error: Repeating the Descriptives

As mentioned above, you want descriptive statistics in the Results Section of your Lab Report, so that the reader can get a picture of what is going on in your data. Are the means looking quite high, or quite different, or quite unusual? What’s the spread of data like?

This is all fab, you want to give the reader this information. But only do it once.

This trap is easier to fall into than you’d think. People sometimes have a table and a graph and mention the descriptive statistics in-text as well.

This is a pretty fundamental error, it loses you word count, and makes the Results Section seem pretty repetitive.

You have a choice. Have your descriptive statistics in a table or a graph or in the text.

When to use each?

Table – this saves word count (tables usually don’t count), it looks really clean, it’s easy to interpret, and most people would expect a table. We often recommend to go with this.

Graph – a well-formatted graph can offer loads of information to your reader. They can get all the information from your study in a glance. This is good to use if you can make good-looking graphs and is sometimes just obviously better than using a table. If you want to persuade the reader of something at a glance, this might be useful.

In-text – sometimes you don’t actually have that much data, so you can simply state the means (M=34.53) and standard deviations (SD=2.73) in-text. If you don’t have much data, it looks weird to have a bare table, or a pretty empty graph. Sometimes in-text descriptives is useful.

Error 3/3

The Error: Interpreting the Results

Remember when we said that the Results Section needs to be crisp, clear and concise?

What we mean is: don’t waffle.

State what the data is and how you calculated it. Done.

State what the descriptives are. Done.

State the inferentials. Done.

Don’t start discussing why you did things in lots of depth, unless you need to justify a novel or rare technique. Don’t have a monologue about how one standard deviations is .03 higher than the other standard deviation. This information is only helping you to leak marks.

You don’t need to start discussing null hypotheses or how your results fit with the literature. Save that for the Discussion Section.

Crisp, clear, concise.

We hope you’ve learnt something in this blog post. Remember to sign up for alerts so that you are always the first person to hear about new content. There’s so much more coming your way.

Keep it going you champion.

Sam and Brad

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