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Truthpizza.org (2014). Misleading Statistics. Retrieved from http://www.truthpizza.org/logic/stats.htm
This particular article can very much contribute to the research topic as the article explicitly identifies the different possible reasons why statistics can be misleading.
Coontz, Stephanie (2013). When Numbers Mislead. Sunday Review. The New York Times. (May 25, 2013) Retrieved from http://www.nytimes.com/2013/05/26/opinion/sunday/when-numbers-mislead.html?_r=0
This contributes a lot to provide more enlighten readers on the topic since specific examples are given that can be used as a solid proof why statistics can be misleading.
Kenelly, Michael J. (2010). 85% of Statistics are False or Misleading. Retrieved from http://scienceblogs.com/worldsciencefestival/2010/08/05/85-of-statistics-are-false-or/
This article contributes a lot for the article as it shows a different view of the possible reasons why statistics can be misleading.
Robbins, Naomi (2012). Another Misleading Graph Not Drawn to Scale. Forbes.com. Retrieved from http://www.forbes.com/sites/naomirobbins/2012/05/10/another-misleading-graph-not-drawn-to-scale/
This author of the article simply commented on an article presented by Jonathan Good who included a Figure that shows the world’s population overtime. In her comment, she mentions why scales are very important in the presentation of statistics because usually, people will not want to see the details of the data when it has already been presented with the use of figures. If scales are not properly made, then there is a tendency that the people who are reading the data will be mislead to. She suggests that proper scaling has to be observed always.
Although, the article focuses on the use of scales for graphs when presenting data, it is very important to the article as it shows additional concrete proofs why statistics can be misleading.
This particular article can very much contribute to the research topic as the article explicitly identifies the different possible reasons why statistics can be misleading.
Coontz, Stephanie (2013). When Numbers Mislead. Sunday Review. The New York Times. (May 25, 2013) Retrieved from http://www.nytimes.com/2013/05/26/opinion/sunday/when-numbers-mislead.html?_r=0
This contributes a lot to provide more enlighten readers on the topic since specific examples are given that can be used as a solid proof why statistics can be misleading.
Kenelly, Michael J. (2010). 85% of Statistics are False or Misleading. Retrieved from http://scienceblogs.com/worldsciencefestival/2010/08/05/85-of-statistics-are-false-or/
This article contributes a lot for the article as it shows a different view of the possible reasons why statistics can be misleading.
Robbins, Naomi (2012). Another Misleading Graph Not Drawn to Scale. Forbes.com. Retrieved from http://www.forbes.com/sites/naomirobbins/2012/05/10/another-misleading-graph-not-drawn-to-scale/
This author of the article simply commented on an article presented by Jonathan Good who included a Figure that shows the world’s population overtime. In her comment, she mentions why scales are very important in the presentation of statistics because usually, people will not want to see the details of the data when it has already been presented with the use of figures. If scales are not properly made, then there is a tendency that the people who are reading the data will be mislead to. She suggests that proper scaling has to be observed always.
Although, the article focuses on the use of scales for graphs when presenting data, it is very important to the article as it shows additional concrete proofs why statistics can be misleading.