Summary of Paulos (2010) Stories vs. Statistics

Qualitative versus quantitative ways of thinking, speaking and doing research have been an ongoing and seemingly never ending debate especially in social sciences disciplines. As discussed in last week’s readings, this is particularly relevant for the growing discipline of social work, which has been traditionally rooted in qualitative approaches and is even to this day reluctant to embrace the post-positivist/quantitative perspective. Paulos’ (2010, October 24) opinion piece in the New York Times on the dichotomy between storytelling and statistics illustrates that in fact we utilize language from both the literary and scientific cultures in our every day lives, often times unbeknownst to us. Even our every day language contains notions of statistics, mathematics and quantitative philosophies, that come to us quite naturally yet unconsciously. Words such as “usual” and “typical” convey notions of central tendency; words such as “likelihood” and “odds” convey notions of probability; words such as “instance” and “example” convey notions of sampling. Thus, even informal storytelling often times requires the use of quantitative dialect; and on the other side of the coin, the communication of the results of statistical analyses require the use of storytelling methods. ┬áIn our every day lives as individuals, as scholars and as researchers, our vocabulary is riddled with the language of both cultures despite our allegiance to one or the other – according to Paulos, it is an unavoidable phenomenon. “With regards to information statistics, we’re a bit like Moliere’s character, who was shocked to find that he’d been speaking prose his whole life” (p. 1 of 4).

Although parts of the opinion article read like the disjointed ramblings of a mathematician mad man that I could not truly grasp, there are still some important points to draw from it. In Paulos’ opinion, one dialect cannot effectively operate without the other – both quantitative and qualitative worlds assist us in responding to what we observe as researchers and communicating those observations with others. The use of both should be encouraged. For example, administering close-ended surveys and questionnaires require reflection on the ordering and phrasing in order to obtain the information we are seeking. Communicating statistical results to social workers or other front line workers requires a certain storytelling ability in order for the findings to make sense and be contextualized in every day client-worker interactions. Although tensions between stories and statistics will always persist, one is just as important as the other, and both cultures need each other in order to make sense to the world.

Statistics One MOOC

Andrew Conway from Princeton psychology teaches a massive open online course on statistics. The course is meant to be comprehensive. I see they are using R and covering many of the concepts that would lay the foundation for our discussion of research design in the phd 724 class. For example, the course covers from null hypothesis significance testing to multiple regression. At least one first year PhD student is taking the course.

Statistics One by Andrew Conway

Another option on the edX MOOC is Stat2.1x: Introduction to Statistics offered in January 2014.


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