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Quantitative research is the expression of results, through numbers. A clear set of documented results can be provided to avenues of research, marketing or advertising, where the results can be interpreted to assess the legitimacy of the findings. This is most effective when we are attempting to gain a snapshot into a user population, i.e. Broadband internet user throughout various sections of Australia.

For arguments sake, I am going to use broadband Internet usage in Australia and the onset of the National Broadband Network (NBN) as an example, to showcase the advantages and flaws of using quantitative research.

The Australian multi-screen report, produced by Oztam Measuring, focused on how Australians viewed entertainment online, collating information on age and types of devices such a phones, tablets, laptops and smart televisions. The report, whilst incredibly detailed in regards to age and devices used, often failed to recognise the economical disparity within the collated data.

At first you might ask, so what? Why does this matter? Lets simplify things for a moment.

If a sample was taken of PlayStation 4 usage in Australia and compared to usage in Malawi (the poorest country in the world with a GDP of US$226.50), you would notice that the Australian results would be astronomically higher than Malawi. Though the economical divide is clearly the answer, it is harder to prove using only quantitative data, rather than blending it with qualitative results. This idea is on an extreme scale, but the same concept can be applied to the economical landscape of Australia. Take the implementation of the NBN as an example; large swathes of the country will not have access for years and what about those that have access, but cannot afford the price? The idea that quantitative data “misses” key elements of measurement, is reiterated by InterAction, an organisation dedicated to reducing international extreme poverty and strengthening human rights, as they state,

“Quantitative correlations produced (e.g., between costs and benefits, gender, and access to services or benefits) may mask or ignore underlying causes or realities.”

 

Quantitative data serves a great purpose in inspecting what particular groups of people like, need or want. It is a perfect form of research for testing any theories of hypothesis surrounding a theory or subject, as it assumes that a sample is representative of a population. However, samples do not always reflect the mentality, economy or even geographical nature of an entire population and this is where quantitative data can become compromised.

 

References

 

ABS. 2015. Internet Activity, Australia, December 2014. [ONLINE] Available at: http://www.abs.gov.au/ausstats/abs@.nsf/mf/8153.0/. [Accessed 23 September 15].

Interaction. 2015. Strengths And Weaknesses Of Quantitative Evaluation Designs. [ONLINE] Available at: http://www.interaction.org/annex-1-strengths-and-weaknesses-quant-evaluation-approaches. [Accessed 24 September 15].

Oztam. 2015. SCREEN TECHNOLOGIES IN AUSTRALIAN HOMES. [ONLINE] Available at: http://www.oztam.com.au/documents/Other/MultiScreenReport_Q1-2015-Final%20amended%20P7.pdf. [Accessed 24 September 15].