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| 2017-02-08: Colourized |
Preface
February 8 2017 article, edited with additions for a posting on academia.edu on November 13 2023.
February 8 2017
Cited
'False precision is incurred when exact numbers are used for inexact notions. When straightforward statements are decked out in numbers well beyond the accuracy of measurement, the precision is false and can mislead an audience into supposing that information is more detailed than is really the case.' (109).
Pirie lists an example where Scots were shown to be 63% more generous that the Welsh. (109). The author asks what the measurement of generosity would be? (109).
I would add that even if the number is accurate, the use of a sample is limited. In contrast, a government census could provide access to populations of Scotland and Wales.
Alan Bryman in his text Social Research Methods explains that a sample is a segment of the population that is selected for research. It is a subset of the population. Bryman (2004: 543).
The recent United States Presidential election and the United Kingdom, Brexit votes demonstrate that statistical samples of populations do not always equate with end election results.
Perhaps the concepts of sample is not emphasized enough in the media?
Examples of false precision:
'Ninety percent of atheists are very immoral.'
'Ninety percent of Christians are using God as a crutch.'
Reason tells me both statements are likely untrue and both lack statistical support.
If someone states:
'I estimate that fifty percent of whales are gay, but I am not certain.'
Reason provides me with uncertainty, not having studied whales. But it lacks statistical support. In contrast, it is not at least, claiming precision.
Pirie reasons that academic departments reply on this type of data, using false precision. (110). Note my point on sample size, as one problem. Academically, I would suggest completely avoiding the use of false precision, and if numbers are used to humbly admit that reasoned deductions and estimations are being used.
BRYMAN, ALAN (2004) Social Research Methods, Oxford, University Press.
PIRIE, MADSEN (2006)(2015) How To Win Every Argument, Bloomsbury, London.
LANGER, SUSANNE K (1953)(1967) An Introduction to Symbolic Logic, Dover Publications, New York. (Philosophy)PIRIE, MADSEN (2006)(2015) How To Win Every Argument, Bloomsbury, London.
Cited
'False precision is incurred when exact numbers are used for inexact notions. When straightforward statements are decked out in numbers well beyond the accuracy of measurement, the precision is false and can mislead an audience into supposing that information is more detailed than is really the case.' (109).
Pirie lists an example where Scots were shown to be 63% more generous that the Welsh. (109). The author asks what the measurement of generosity would be? (109).
I would add that even if the number is accurate, the use of a sample is limited. In contrast, a government census could provide access to populations of Scotland and Wales.
Alan Bryman in his text Social Research Methods explains that a sample is a segment of the population that is selected for research. It is a subset of the population. Bryman (2004: 543).
The recent United States Presidential election and the United Kingdom, Brexit votes demonstrate that statistical samples of populations do not always equate with end election results.
Perhaps the concepts of sample is not emphasized enough in the media?
Examples of false precision:
'Ninety percent of atheists are very immoral.'
'Ninety percent of Christians are using God as a crutch.'
Reason tells me both statements are likely untrue and both lack statistical support.
If someone states:
'I estimate that fifty percent of whales are gay, but I am not certain.'
Reason provides me with uncertainty, not having studied whales. But it lacks statistical support. In contrast, it is not at least, claiming precision.
Pirie reasons that academic departments reply on this type of data, using false precision. (110). Note my point on sample size, as one problem. Academically, I would suggest completely avoiding the use of false precision, and if numbers are used to humbly admit that reasoned deductions and estimations are being used.
BRYMAN, ALAN (2004) Social Research Methods, Oxford, University Press.
PIRIE, MADSEN (2006)(2015) How To Win Every Argument, Bloomsbury, London.
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November 13 2023
Cited
'(also known as: over-precision, false precision, misplaced precision, spurious accuracy)
Description: Using implausibly precise statistics to give the appearance of truth and certainty, or using a negligible difference in data to draw incorrect inferences.'
Cited
'Tour Guide: This fossil right here is 120,000,003 years old.
Guest: How do you know that?
Tour Guide: Because when I started working here three years ago, the experts did some radiometric dating and told me that it was 120,000,000 years old.
Explanation: Although more of a comedy skit than anything else, this demonstrates the fallacious reasoning by the tour guide in her assumption that the dates given to her were precise to the year.'
Cited
'Tip: Don’t confuse fake precision with real performance.'
Huff, D. (1993) How to Lie with Statistics (Reissue edition). New York: W. W. Norton & Company.
Example
I took a walk in the back 40 forty (40 acers of underdeveloped land).
I took a walk in the back 40 forty (40 acers of underdeveloped land).
Cited
'a remote and uncultivated or undeveloped piece of land of indefinite size (as on a farm)'
“Back forty.” Merriam-Webster.com Dictionary, Merriam-Webster, https://www.merriam-webster.com/dictionary/back%20forty. Accessed 13 Nov. 2023.
It would be false precision and fallacious to assume that the underdeveloped land I walked in was actually 40 acres. In fact, the land I had in mind, from my past, was actually approximately five acres.
Cited
'Overprecision
Alias:
Fake Precision1
False Precision2
Misplaced Precision3
Spurious Accuracy4'
Cited
