Arunabh Ghosh
- Published in print:
- 2020
- Published Online:
- September 2020
- ISBN:
- 9780691179476
- eISBN:
- 9780691199214
- Item type:
- chapter
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691179476.003.0004
- Subject:
- History, Asian History
This chapter explores how this new understanding of statistics became dominant in the 1950s and how it affected the valuation of key concepts and methods. It first unpacks attempts at demarcation by ...
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This chapter explores how this new understanding of statistics became dominant in the 1950s and how it affected the valuation of key concepts and methods. It first unpacks attempts at demarcation by focusing on the nearly decade-long sequence of publications that sought to criticize Anglo-American “bourgeois” statistics and its practitioners. The chapter then shifts to the changes in statistical education and to the debates over the content of statistics. In broad terms, the consequences of this transition are well known: as a social science, statistics dealt with the social world rather than the natural world. As a result, it was bifurcated from what was seen as the abstract and formal theorizing of mathematical statistics, which was, in turn, banished to departments of mathematics.Less
This chapter explores how this new understanding of statistics became dominant in the 1950s and how it affected the valuation of key concepts and methods. It first unpacks attempts at demarcation by focusing on the nearly decade-long sequence of publications that sought to criticize Anglo-American “bourgeois” statistics and its practitioners. The chapter then shifts to the changes in statistical education and to the debates over the content of statistics. In broad terms, the consequences of this transition are well known: as a social science, statistics dealt with the social world rather than the natural world. As a result, it was bifurcated from what was seen as the abstract and formal theorizing of mathematical statistics, which was, in turn, banished to departments of mathematics.
Bruce Bower
- Published in print:
- 2011
- Published Online:
- May 2016
- ISBN:
- 9780262016032
- eISBN:
- 9780262298957
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262016032.003.0010
- Subject:
- Psychology, Health Psychology
At a time when financial pressures and a digital revolution threaten the survival of many media outlets, a focus on statistical literacy can improve health and medical reporting and perhaps foster ...
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At a time when financial pressures and a digital revolution threaten the survival of many media outlets, a focus on statistical literacy can improve health and medical reporting and perhaps foster survival-enhancing changes in how the media cover these topics. Journalists often lack knowledge about statistical thinking. First reports of scientific findings, advances in “hot” research fields, and results that contradict previous assumptions draw special attention from the media, but underlying statistical problems and uncertainties in such studies are rarely mentioned in news stories. Clinical trials, significance testing, and meta-analyses create particular confusion for journalists. Possible ways to remedy this problem include early statistical education, professional development courses, online assistance sites, and efforts to use personal stories to illuminate the predictive value of medical tests.Less
At a time when financial pressures and a digital revolution threaten the survival of many media outlets, a focus on statistical literacy can improve health and medical reporting and perhaps foster survival-enhancing changes in how the media cover these topics. Journalists often lack knowledge about statistical thinking. First reports of scientific findings, advances in “hot” research fields, and results that contradict previous assumptions draw special attention from the media, but underlying statistical problems and uncertainties in such studies are rarely mentioned in news stories. Clinical trials, significance testing, and meta-analyses create particular confusion for journalists. Possible ways to remedy this problem include early statistical education, professional development courses, online assistance sites, and efforts to use personal stories to illuminate the predictive value of medical tests.
