Writing week seven

Description and analysis

Introduction

Over the next two weeks we're going to practise separating out descriptive from analytical writing by looking at what kind of language we use to report results and discussions. These sections appear in journal articles across disciplines, and you may have to write them yourselves if your future studies require you to collect and report data. Studying the language of these two sections and how they differ will also help us develop our own voice and argument in our writing.

Discussion

Organise yourselves into four separate groups. Each group looks at one of the charts describing an aspect of global population trends, which have been taken from Our World in Data. As your group discusses and makes notes, think about:

  • What are the most significant details conveyed by the data? Are there any interesting contrasts?
  • What predictions would you make for future trends?
  • What do you think might be some of the causes behind the trends?
  • What might be the political, economic, social, and/or technological (PEST) implications of these trends?

Presentation of findings

Once you've completed your discussion, take turns to present the data to the rest of the class. First describe the data, and then offer your group's analysis and discussion.

Describing and analysing

Earlier this term we looked at using evaluative language and developing an authorial voice in writing. We also saw in the Hans Rosling talk earlier this term that there's a distinction between just describing the data that we see, and offering our own analysis by looking at possible causes of any trends or anomalies, and by making predictions about the future. Distinguishing between description and analysis when talking about data is a very useful skill that is required in many academic disciplines.

Task one

The sentences on the left refer to the data below on life expectancy around the world. Which would you class as description, and which are analysis?

You can isolate individual countries by clicking on them, and if you click the chart tab at the bottom you can directly compare two or more countries.

Task two

Work with a partner and explore the data set in more detail. Try to come up with two more points for description and analysis. Use the Academic Phrasebank's section on describing trends to help you.

Description

When we describe quantitative data we avoid verbalising every aspect, and instead focus on:

  • Surprising features
  • Striking contrasts
  • Overall trends

This section only talks about the data that we can see.

Analysis and discussion

Analysis links the data to the real world, so for analytical writing we need to discuss external factors:

  • What are the possible causes for data trends?
  • What does the data tell us about the world?
  • What other factors are affected by these data?
  • What further questions are raised?

Language for analysis

In week ten of last term (the language of conclusions), we started to look at the idea of hedging language, where we express how certain we are that what we're saying is true. As with conclusions, hedging language is also useful for analysis and discussion as described above.

Task three

  1. Decide which of the below examples are more tentative and which are more certain:
    • This clearly demonstrates that...
    • This could partially explain why...
    • This may perhaps indicate the need to...
    • We can conclude from this that...
    • These data tell us that in future it will...
  2. Look at some further examples from UEfAP, and work through the set of exercises at the bottom of the page.

Task four - free writing practice

We're going to write a paragraph which draws together the language techniques that we've looked at above. Your teacher will open up an assignment on Google Classroom.

  • Watch the video clip and describe what's being shown, remembering to focus on surprising features, striking contrasts and general trends.
  • Then, write a short analysis which discusses the possible causes behind some of the trends, future predictions, and implications (for example, environmental, social, technological).