How to Read Numbers by Tom and David Shivers uncovered many statistical perspectives, and anomalies depending on the point of view. The book was insightful, and detailed, and provided a beneficial recap of many math courses from my past. I enjoyed unraveling statistical positioning however I noticed a variant in my personal synopsis almost immediately. I am guilty of preconceived skepticism and I warn readers of my own prejudice.<\/p>\n
The co-authors are cousins who are extremely talented and brought a light-hearted personal touch to the reading. I appreciated it considering the book\u2019s focus dissects a subject (math\/statistics) that many would run from. I find it interesting that math is a discipline that can excite or scare people. \u00a0I particularly enjoy math and so do my sons. My wife, mother, and daughter have an opposite outlook that tends to be credulous.\u00a0 Is math preference gender specific? Or is it the influence of using math that plays more of a gender role? Perhaps gullibility is gender specific? I paused for research and found that many of us are guilty of gender stereotyping and it\u2019s prevalent in many cultures. For example, my wife is immediately a target in a car dealership or oil change scenario. In the car salesman\u2019s defense, she is also extremely trusting with almost anyone and has even accidentally assisted in theft in our own business. She rarely questions the information presented and a trained individual can read her like a children\u2019s book.\u00a0 She is off the charts in science and medicine but below average when it comes to anything deceptive or criminal. The research supports this commonality among women in many instances, however, El Andrews of the Berkeley Hass School of Business claims this paradox is not necessarily a chromosomal disparity.\u00a0 \u201cThe mere perception that women are more gullible exposes them to more deception in reality. Though it\u2019s not clear that women actually are easier to mislead, the perception itself prompts more of their counterparts in negotiations to make misleading and even blatantly false claims. As a result, women are deceived more often than men.\u201d[1]<\/a><\/p>\n After completing the book and spending an excessive amount of unnecessary time researching fraudulent statistics in today\u2019s society, I concluded that bias exists in gender situations but also in any emotional situation. Mark Twain claimed, \u201cThere are liars and statistics.\u201d Perhaps a better quote would be \u201cthere are liars and liars that use statistics.\u201d I believe this to be true with the majority of corporate America, media, and government. \u00a0Statistics hold a great deal of significant weight and \u201cmisunderstanding the statistics can lead to bad decisions,\u201d political outcomes, power, control, corruption, and financial gain for certain institutions.[2]<\/a> \u00a0I searched for scholarly material and hard data, which is readily available from a number of perspectives, however, I was left unsatisfied due to many examples of misinformation and \u201ccherry-picked\u201d figures. \u201cSelling\u201d something emerges as the common denominator.\u00a0 Whether it is views, clicks, a product, a vaccine, or an idea, the presentation of the \u201cfacts\u201d appears to be a muddy playground of codology.<\/p>\n I was amazed, but not surprised to find consistent and \u201cobvious\u201d headline bias in the news and research. Regardless of the data presented, I noticed a correlation in the titles of the articles or broadcasts that suggested a certain outcome or call to action. The authors of How to Read Numbers<\/em> define these demonstrations as HARKing, or \u201cintentionally selecting criteria to meet an intended outcome.\u201d [3]<\/a> In regard to the pandemic, misinformation became the norm over the years and incredulous for opposing parties. I observed many instances of \u201csocio-cognitive polarization,\u201d fake news, and fear-mongering that have scared and divided the masses.[4]<\/a> The pandemic was extremely mismanaged, censored, and calculated. \u201cIn times of uncertainty, people often seek out information to help alleviate fear, possibly leaving them vulnerable to false information. During the Covid-19 pandemic, we attended to a viral spread of incorrect and misleading information that compromised collective actions and public health measures.\u201d[5]<\/a> The powers at large were extremely aware of this and turned our fear into record-breaking profits.<\/p>\n Covid-19 was more than a virus; it was a tool used in a movement of epic power and dominance on a global scale.\u00a0 I quickly noticed that even the research on misinformation was also subject to bias so I concluded my investigation. This book opened my eyes to the art of misleading individuals through numbers.\u00a0 Reading data is a language in itself that requires a level of hermeneutics for proper interpretation. I believe the media and many corporations capitalize on the idea that many will not challenge the data if presented and cited suitably. \u00a0The authors exposed many examples of preferential Covid-19 data and we have all experienced the results of this massive dark undertaking.<\/p>\n Trust is the major outlier in my own statistical digestion. \u00a0I have less trust in the media and government after this pandemic and even more faith in God. \u201cI appeal to you, brothers, to watch out for those who cause divisions and create obstacles contrary to the doctrine that you have been taught; avoid them. For such persons do not serve our Lord Christ, but their own appetites, and by smooth talk and flattery they deceive the hearts of the naive.\u201d[6]<\/a><\/p>\n <\/p>\n [1]<\/a> Andrews, El. 2014. \u201cPerception and Reality: Why Women Are More at Risk of Being Duped in Business \u2013 Archive of the Institute for Business and Social Impact.\u201d August 11, 2014. Link<\/a><\/p>\n [2]<\/a> Chivers, Tom, and David Chivers. 2022. How to Read Numbers<\/i>. Weidenfeld & Nicolson. p. 3<\/p>\n [3]<\/a> Ibid, 115<\/p>\n [4]<\/a> \u201cLibrary Guides: Savvy Info Consumers: Detecting Bias in the News.\u201d 2017. Uw.edu. University Libraries, University of Washington. 2017. Link<\/a>.<\/p>\n [5]<\/a> Frontiers. Peer Reviewed Articles; “Going Viral\u201d 2014. Link<\/a><\/p>\n [6]<\/a> Romans 16:17-18, ESV<\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":" How to Read Numbers by Tom and David Shivers uncovered many statistical perspectives, and anomalies depending on the point of view. The book was insightful, and detailed, and provided a beneficial recap of many math courses from my past. I enjoyed unraveling statistical positioning however I noticed a variant in my personal synopsis almost immediately. 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