Damned lies and statistics: Untangling numbers from the media, politicians and activists
By J. Best
Glossary Terms
Practical significance - a conclusion determined by an effect size statistic that indicates a research finding is practically important or useful in real life.
http://www.utexas.edu/academic/ctl/assessment/iar/glossary.php
Statistical significance - A mathematical technique to measure whether the results of a study are likely to be true. Statistical significance is calculated as the probability that an effect observed in a research study is occurring because of chance. Statistical significance is usually expressed as a P-value. The smaller the P-value, the less likely it is that the results are due to chance (and more likely that the results are true). Researchers generally believe the results are probably true if the statistical significance is a P-value less than 0.05 (p<.05).
US Department of Health & Human Services http://effectivehealthcare.ahrq.gov/index.cfm/glossary-of-terms/?pageaction=showterm&termid=67
Interpretive science - Explanation based on observation and description of entire objects or systems rather than isolated parts.
http://highered.mcgraw-hill.com/sites/0070294267/student_view0/glossary_e-l.html
Critical Science - The basic tenet of the critical science approach is that people need to think about improving their living conditions rather than accepting and coping with their present conditions. That improvement is contingent upon people being conscious of social realities that exploit or dominant them and then demanding liberation from these forces. If people can be taught to recognize that their condition can be improved, they are more likely to work together to achieve this improvement, liberation, freedom.
McGregor, S. (2003). Critical Science - A Primer Kappa Omicron Nu FORUM, 15(1) np. Available at:
http://www.kon.org/archives/forum/15-1/nmcgregorcs.html
Statistics - The mathematics of the collection, organization, and interpretation of numerical data, especially the analysis of population characteristics by inference from sampling.
http://www.thefreedictionary.com/statistics
Mutant Statistics - stretched, twisted, distorted or mangled versions of original figures
Best, J. (2001) Damned lies and statistics: Untangling numbers from the media, politicians and activists. Berkley, CA: University of California Press
Quotes
“Statistics are rarely neutral.” (Bracey, 2006, pg. 78)
I made note of this quote because I had never really thought of this before. When statistics are presented they are usually used to persuade or convince people of a particular point of view or to give them evidence to support a claim.
“You need more than one statistic to get a full picture of just about anything.” (Bracey, 2006, pg. 78)
I have to admit that I have never thought about the idea that people making claims may only use one statistic or study to support their claim and the only real way to conclusively prove something would be to have several studies performed by various researcher that back up the same hypothesis.
“Most of the time, most people simply accept statistics without question” (Best, 2001, pg. 4)
This was a quote that Bracey put in his article from another author. My question is, “Why don’t we question statistics?” Is it simply a matter of interest or laziness; or is it the belief and desire to believe that scientific researchers will not lead us wrong. Is it our belief that they are objective and that they are just telling us the truth. Maybe that is one of the limitations or downfalls of empirical research.
References
Bracey, Gerald W. (2006). How to Avoid Statistical Traps. Educational Leadership, 63(8), 78-82.
Ritchey, S. J. (1989). Role of Empirical Science in Present Day Home Economics practice. In F. H. Hultgren & D. L. Coomer (Eds.), Alternate modes of inquiry in home economics research, pp. 24 - 29. Yearbook 9, American Home Economics Association. Peoria, IL: Glencoe.
Copa, G. H. (1989). Troubling Concerns with the Empirical/Analytic Mode of Research. In F. H.Hultgren & D. L. Coomer (Eds.), Alternate modes of inquiry in home economics research, pp. 30 - 33. Yearbook 9, American Home Economics Association. Peoria, IL: Glencoe.
McGregor, S. (2003). Critical Science - A Primer Kappa Omicron Nu FORUM, 15(1) np. Available at: http://www.kon.org/archives/forum/15-1/nmcgregorcs.html
Best, J. (2001) Damned lies and statistics: Untangling numbers from the media, politicians and activists. Berkley, CA: University of California Press
Practical significance - a conclusion determined by an effect size statistic that indicates a research finding is practically important or useful in real life.
http://www.utexas.edu/academic/ctl/assessment/iar/glossary.php
Statistical significance - A mathematical technique to measure whether the results of a study are likely to be true. Statistical significance is calculated as the probability that an effect observed in a research study is occurring because of chance. Statistical significance is usually expressed as a P-value. The smaller the P-value, the less likely it is that the results are due to chance (and more likely that the results are true). Researchers generally believe the results are probably true if the statistical significance is a P-value less than 0.05 (p<.05).
US Department of Health & Human Services http://effectivehealthcare.ahrq.gov/index.cfm/glossary-of-terms/?pageaction=showterm&termid=67
Interpretive science - Explanation based on observation and description of entire objects or systems rather than isolated parts.
http://highered.mcgraw-hill.com/sites/0070294267/student_view0/glossary_e-l.html
Critical Science - The basic tenet of the critical science approach is that people need to think about improving their living conditions rather than accepting and coping with their present conditions. That improvement is contingent upon people being conscious of social realities that exploit or dominant them and then demanding liberation from these forces. If people can be taught to recognize that their condition can be improved, they are more likely to work together to achieve this improvement, liberation, freedom.
McGregor, S. (2003). Critical Science - A Primer Kappa Omicron Nu FORUM, 15(1) np. Available at:
http://www.kon.org/archives/forum/15-1/nmcgregorcs.html
Statistics - The mathematics of the collection, organization, and interpretation of numerical data, especially the analysis of population characteristics by inference from sampling.
http://www.thefreedictionary.com/statistics
Mutant Statistics - stretched, twisted, distorted or mangled versions of original figures
Best, J. (2001) Damned lies and statistics: Untangling numbers from the media, politicians and activists. Berkley, CA: University of California Press
Quotes
“Statistics are rarely neutral.” (Bracey, 2006, pg. 78)
I made note of this quote because I had never really thought of this before. When statistics are presented they are usually used to persuade or convince people of a particular point of view or to give them evidence to support a claim.
“You need more than one statistic to get a full picture of just about anything.” (Bracey, 2006, pg. 78)
I have to admit that I have never thought about the idea that people making claims may only use one statistic or study to support their claim and the only real way to conclusively prove something would be to have several studies performed by various researcher that back up the same hypothesis.
“Most of the time, most people simply accept statistics without question” (Best, 2001, pg. 4)
This was a quote that Bracey put in his article from another author. My question is, “Why don’t we question statistics?” Is it simply a matter of interest or laziness; or is it the belief and desire to believe that scientific researchers will not lead us wrong. Is it our belief that they are objective and that they are just telling us the truth. Maybe that is one of the limitations or downfalls of empirical research.
References
Bracey, Gerald W. (2006). How to Avoid Statistical Traps. Educational Leadership, 63(8), 78-82.
Ritchey, S. J. (1989). Role of Empirical Science in Present Day Home Economics practice. In F. H. Hultgren & D. L. Coomer (Eds.), Alternate modes of inquiry in home economics research, pp. 24 - 29. Yearbook 9, American Home Economics Association. Peoria, IL: Glencoe.
Copa, G. H. (1989). Troubling Concerns with the Empirical/Analytic Mode of Research. In F. H.Hultgren & D. L. Coomer (Eds.), Alternate modes of inquiry in home economics research, pp. 30 - 33. Yearbook 9, American Home Economics Association. Peoria, IL: Glencoe.
McGregor, S. (2003). Critical Science - A Primer Kappa Omicron Nu FORUM, 15(1) np. Available at: http://www.kon.org/archives/forum/15-1/nmcgregorcs.html
Best, J. (2001) Damned lies and statistics: Untangling numbers from the media, politicians and activists. Berkley, CA: University of California Press