Skip to main content

Research Guide: Data collection techniques

This Guide provides post graduate students with the tips and tools necessary to successfully complete their research.

Google Data Search

Statistical Software Access - contacts and 'how-to'

Various statistical software exist, that can make life easier when analyzing your data. 

IBM SPSS and Atlas.ti are both uploaded on all Hatfield and Groenkloof Research Commons computers.  

To have either of these installed on your personal computer, email your enquiry to help@it.up.ac.za. Please note: this can only be done for registered UP students.


The Research Commons computers are now equipped with R -  a free tool with a user-friendly interface for managing and analyzing your research data. is a popular alternative to other statistical programs, such as SPSS, SAS, and Python. Find out more about the basics of R here: https://www.datamentor.io/r-programming/


 

For access to Qualtrics for your personal computer, please:

  • Contact  Charl.joubert@up.ac.za and request to be added to the IT Services portal
  • Once Charl has confirmed that your profile has been added, follow the steps outlined here.

Past presentations

There are no Past presentations available at present.

Data collection techniques

Under the main three basic groups of research methods (quantitative, qualitative and mixed), there are different tools that can be used to collect data. Interviews can be done either face-to-face or over the phone. Surveys/questionnaires can be paper or web based. Observations and experiments can be conducted to collect either quantitative, qualitative or a mixture of the two methods. Records can also be used to study previous information by other researchers.  

Tips

  • Organise collected data as soon as it is available
  • Begin with the end in mind - know what message you want to get across and then collect data that is relevant to the message
  • Collect more data
  • Create more data
  • Regularly run experiments or collect data
  • Challenge your assumptions
  • Set reasonable expectations
  • Take note of interesting or significant data
  • Quantity is good but quality is even better

Recommended Quantitative Data Collection books

Recommended Qualitative Data Collection books