This video outlines 5 tips to help you analyse, interpret and present data effectively.
Tip number 1: Keep your aim and audience in mind at all times. This will help you to
stay on task.
Before you start interrogating the data, develop a list of questions to guide your thinking.
Let’s imagine that you have been asked to respond to the following task.
Senior Management at Tea for Three have provided data on attendance at staff training workshops
for the past 5 years and participant evaluation surveys.
They have asked you to evaluate staff satisfaction with the program and recommend any changes.
You might start by asking: Has attendance gone up, down or stayed
the same in this period?
Has participant satisfaction gone up, down or stayed the same in this period?
Are these changes significant, moderate or minimal?
Are trends the same for all workshop topics?
Does qualitative data support the quantitative data?
Approaching the task in this way, will help you to take a critical stance.
Tip number 2: Organise, summarise and manipulate data to notice relationships, patterns or trends.
We often use spreadsheets, databases, tables, or graphs to do this.
If you have data in a table, you can manipulate it using functions such as sum, average or mean.
Going back to our task, this table shows raw data on attendance for the past 5 years.
Let’s use sum to to give us a total, and then calculate the percentage change each year.
What do you notice?
From the table, I can now see that overall attendance has been stable over the past 5 years,
but that two workshops have become more popular, and two have become less so.
If trends are difficult to spot, try changing the format of the data.
If we look at the same data in a bar chart, these trends become much clearer.
We can see a very clear decline for word processing and a significant increase in digital tools
for collaboration.
Once you’ve noticed the trends and patterns, you can begin your analysis.
What do you notice?
What does this indicate?
From the data we’ve looked at we can see that overall attendance at workshops remained stable
since 2015.
Indicating that there is a demand for professional development.
Increasing attendance in both Effective presentations
and Digital tools for collaboration, indicate that these topics are of particular interest or relevance.
And decreasing attendance at Word processing
and Emails, indicates these topics might be less useful or interesting.
And then, interpret the data.
What does this mean for Tea for Three and their planning?
We might conclude, or recommend, that while demand for training is consistent, the topics
should be reviewed.
When you’re dealing with qualitative data (words, observations, pictures, or symbols),
try to identify themes or categories.
Try: comparing responses by question, topic, time period or event.
For example, if you have 10 interviewees you might compare all 10 answers
to question 1.
Reviewing each case or person holistically to build a profile.
For example, analyse respondent 1’s interview in full, then move on to respondent 2.
Categorising and coding - this is where you label different themes as you notice them.
For example, you could use [U] for urban, [S] for suburban and [R] for rural when dealing
with geographical locations.
Pause the video, take a moment to read the following excerpts from participants at the workshops.
What themes do you notice?
I noticed three main themes: flexibility, topic choice and delivery format – which
I’d code, like this.
Once you’ve organised your data, for example like this, the next step is to interpret it.
What does this mean for Tea for Three and their training planning?
How does this link to the quantitative data?
What recommendations can we make?
Here are some possible recommendations.
Tip number 3 – present your data in a format that maximises clarity and impact.
Ask yourself whether it makes most sense to include it in text, tables, or charts.
Let’s compare the chart and the table we made earlier.
If you wanted to highlight the trends in individual workshop attendance, which do you think shows
this most effectively - the chart, or the table?
Most people would agree that the chart shows the trend more effectively. It’s a nice
clear, visual representation.
We can see the rise and fall.
Tip number 4 - label, refer to, and explain any data in text.
You should also make sure that you place the data and the text close to each other.
For instance, don’t have a table on page 3, that you only refer to on page 6.
Take a minute to read the example on the right.
In this example, you can see that the chart is labelled, referred to clearly in text
and then explained, rather than described.
A common mistake is to simply describe the content of a chart or table in text. But this
does not add any value or meaning.
Instead, use language that indicates analysis, such as (dropped significantly), interpretation
(suggesting a decline), and implication (indicating that these topics lack relevance).
This is really important in helping your reader to follow your ideas.
So, tip 5 is to use this language in your writing.
Here we have examples of language for reporting on or drawing attention to aspects of the data.
For example, you can refer to a table or graphic, indicate a peak or trough, proportion or percentage
or perhaps a contribution.
While you need to use this language, you also need to move onto interpretation.
For example: explaining meaning or importance, making projections, or signalling implications.
In sum, we’ve worked through 5 tips to help you analyse, interpret and present data effectively.
Keep your aim & audience in mind at all times. Organise, summarise and manipulate the data.
The format should maximise clarity and impact.
Label, refer to and explain all data in text.
And signal analysis & interpretation to your reader.
Good luck with your analysis!
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