Enhancing Statistical Knowledge in Sociology

English: Normal distribution curve that illust...

English: Normal distribution curve that illustrates standard deviations (Photo credit: Wikipedia)

This week I attended two events to encourage the development and use of statistical and quantitative knowledge in A level and undergraduate level sociology.

The Royal Statistical Society invited me to the first event in London, The Future of Statistics in Our Schools and Colleges, and the second event was part of the Higher Education Academy‘s Science, Technology, Engineering and Mathematics (STEM) programme. Both were looking in some degree at A level and undergraduate level teaching of statistics and quantitative methods.

I was pleased to share both my experiences and those of my SOA colleagues of using quantitative methods and statistics as a social researcher and sociologist outside of academia and as someone who has trained others in the use of these methods. By sharing this knowledge hopefully we have provided an understanding of the sort of skills that will be required by students in the workplace and the advantages some ability and confidence with quantitative methods can provide.

Anecdotally, for example, my colleagues and I were all dependent, at least in part, on our knowledge of quantitative methods to be doing the jobs we are.

For the most part, the following skills in statistics and quantitative methods are advantageous:

  • Fractions, proportions and percentages.
  • Descriptive statistics, such as mean, median and mode, standard deviation, and confidence intervals.
  • Frequencies.
  • Understand sampling and population.
  • Statistical significance (p value).
  • Communication skills – to share findings with others, usually those who do not have knowledge of these techniques.

Nail these and you’re massively more employable as a social researcher.


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