Combating Data Manipulation: Introduction

After reading a few books on data presentation and statistics and probability theory, I have decided to create a 10-post series about things everyone should know about data.  As Charles Seife mentions in the first few paragraphs of his book Proofiness, putting numbers to an opinion or thought tend to make people believe the opinion more than without that mathematical or numerical backing.  Seife, in his introduction, uses Joe McCarthy as an example of this: when he declared that the State Department harbored communists, his argument got even more persuasive when he declared that he could name 205 of them.  Afterwards, that number fluctuated from 207 to 57 to 81 to even less than those, but what mattered was that McCarthy had a number to back his statement up.

Sooner or later, everyone will encounter some data set, graph, chart, or statistic that is either made up entirely or somehow false.  Unfortunately, a lot of people end up basing opinions or votes on these mathematical falsehoods simply because the skills of identifying data manipulation are not widely taught.

These posts will have applications in statistics, economics, political science, as well as many other fields, approached from a mathematical and statistical perspective.  And, while I will be using books such as Seife’s Proofiness and Leonard Mlodinow’s book The Drunkard’s Walk: How Randomness Rules Our Lives, I will verify that the information I post here is as accurate as I can make it.

Works Cited:

Charles Seife, Proofiness

Leonard Mlodinow, The Drunkard’s Walk: How Randomness Rules Our Lives


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