If you would like to test your maths skills, complete the Numeracy Success Indicator (NSI)
As a student in Humanities or Social Sciences, even if you are not doing calculations, you need to understand what various sets of data mean. For example,
Even if you are engaging in qualitative research (‘how’ and ‘why’ type questions), quantitative (numerical) data is useful for context and to understand the bigger picture of events or case studies. Although numbers are not stated, quantitative calculations are often used as part of fundamental analysis. For instance,
These statements arise from basic arithmetic that you probably learnt at school:
Much of the data you will use as an undergraduate in the Humanities and Social Sciences will be provided for you, but there are also programs which will do the calculations for you, such as:
Your lecturer may also suggest other software, but make sure you get some training in how to use it! So look out for any training that the university is offering.
As more and more information becomes available in digital format, there is more statistical analysis to do.
If you know how results are calculated, you can interpret them correctly.
This Achieve@Uni page focuses on the presentation of data rather than calculations themselves, but other modules in this section of Achieve@Uni outline the basic principles for you. You may also find it useful to look at Rachel Chrastil’s course ‘Quantitative Literacy and the Humanities'.
If working with numbers makes you feel uncomfortable or anxious then begin by looking the Maths Anxiety page in our Maths module. Once you understand basic principles of sorting or grouping data, it will feel less overwhelming and more manageable.
For more information on writing about statistical information look at the United Nations Economic Commission for Europe, ‘Making Data Meaningful. Part 1: A guide to writing stories about numbers’.
Two or more events that happen to coincide are not necessarily related so be careful what you infer from statistical data.
There may be a third variable that accounts for the correlation or it might just be a coincidence. Even if there is a relation this does not explain why it is occurring or even the direction of the cause and effect.
For example, the consumption of doughnuts might strongly correlate with improvements in first year test scores. But this does not mean that eating doughnuts will improve your test results – and in this case, it is most likely a coincidence!
For more information on variables see the Achieve@Uni Statistics module.
In some Humanities and Social Science subjects, even there are no specific numbers, the thought processes of logic and probability are valuable.
This means that the critical thinking developed in your studies can be applied to statistical results to consider the value of the data, the methods of collection, the extrapolation of results or biases in the sample.
To explore these concepts further and work through some practice exercises for the Humanities and Social Sciences, the following resources provide a great way to begin!