{"id":35623,"date":"2024-02-08T10:31:46","date_gmt":"2024-02-08T18:31:46","guid":{"rendered":"https:\/\/blogs.georgefox.edu\/dlgp\/?p=35623"},"modified":"2024-02-08T10:33:21","modified_gmt":"2024-02-08T18:33:21","slug":"understanding-is-everything-let-your-curiosity-lead-the-way","status":"publish","type":"post","link":"https:\/\/blogs.georgefox.edu\/dlgp\/understanding-is-everything-let-your-curiosity-lead-the-way\/","title":{"rendered":"Understanding is everything: let your curiosity lead the way"},"content":{"rendered":"

In a world where we tend to be either overly suspicious or not suspicious enough of the research and statistics at the core of many of our beliefs, Tim Harford\u2019s\u00a0 \u201cThe Data Detective: Ten Easy Rules to Make Sense of Statistics\u201d\u00a0 offers a solution for how to find a healthy balance where we learn to filter what we hear through utilizing our mind, rather than simply our emotions. Hartford claims that a large part of the problem when it comes to making sense of statistics and using them as helpful tools for understanding is that we rely too heavily on emotions \u2013 bringing our fears into the mix and either blindly believing or dismissing data we hear,\u00a0 based off of the gut reactions it stirs, rather than pausing to think about if what we heard was true and if we value the truth.\u00a0 <\/span>\u00a0<\/b>His book provides insight into how we interpret and use statistics to inform our positions on issues.<\/span><\/p>\n

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In an interview at the Rotman School of Management, Harford addresses valid concerns about statistics as a form of factual data while still making a case for us not to give up on them stating, \u201cStatistics can be used to lie, just as words can be used to lie, but we wouldn’t say \u201c oh some people sometimes lie with words and therefore I’m never going to listen to anything anybody ever says\u2026because I don’t want any of those nasty lies…this would be absurd.\u201d [1]\u00a0<\/span><\/p>\n

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I appreciate this example highlighting the \u201c absurdity\u201d for it shows us how quick we as humans are to jump into full-fledged black-and-white thinking \u2013 completely writing things off and erasing any value add they may have.\u00a0 Yet when we apply the same sweeping generalizations to other things in our lives, like human relations in this example, we can more easily see the error of our generalized thinking. <\/span>\u00a0Hardford\u2019s <\/span>main argument is that<\/span> statistical data is <\/span>a reliable method of discerning facts and forming conclusions about human behavior and societal issues, however only if we are selective in how we look at and interpret the data we consume, because it is certainly not without bias. The key is in learning<\/span> how <\/span><\/i>to examine and apply statistical data to bring meaning to our lives and to understand the world around us better. [2]\u00a0<\/span><\/p>\n

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When it comes to the statistics we\u2019re digesting, a question we should all be asking ourselves is if we can trust ourselves to be able to figure out what is going on.\u00a0 Harford aims to help readers increase their self-trust by offering tools to easily assess statistics for themselves. I will explore this idea of building confidence and self-trust later.\u00a0\u00a0<\/span><\/p>\n

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First, let\u2019s touch on a few of the many reasons why statistics cannot be trusted in today’s world. Despite being such an integral part of our everyday lives \u2013\u00a0 from sports to business to politics \u2013 the reality is that they can still be false or misinterpreted. Statistics are often intentionally manipulated to cause misinterpretation by the average consumer, twisted in clever ways that push specific opinions and narratives [3].\u00a0 From cherry-picking statistics to serve one’s needs, pulling small sample sizes to exaggerate impact, or even implying correlation as causation, all of these are things we must be aware of before we take statistical data at face value. While this highlights why we shouldn’t simply accept them, we should not simply reject them either. Both of these responses require little brain power.\u00a0<\/span><\/p>\n

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When filtering data we need to examine variations present in the data such as proximity, population density, income, age, genetic makeup, height, and weight [4]. We also need to pay extra attention to the relative adjectives used \u2013 both in terms of how a study defines something as well as in understanding that respondents’ understandings may differ. Another thing to be aware of is the accuracy of a respondent’s data when being surveyed \u2013 were they fully honest?\u00a0<\/span><\/p>\n

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Being exposed to the many ways statistical data can be deceptive and misleading is an interesting awakening because it highlights the danger of half-truths. Charles Seife, an American author and journalist, explores this idea in his book Proofiness: The Dark Arts of Mathematical Deception. Seife highlights the macro implications of this when he says that these manipulative tactics regarding how statistical data is presented can be used \u201cto bring down beloved government officials and to appoint undeserving ones (both Democratic and Republican), to convict the innocent and acquit the guilty, to ruin our economy, and to fix the outcomes of future elections.\u201d[5]<\/span><\/p>\n

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If the average consumer can be fed data with a sliver of truth, many will cling to that, believing whatever message is being pushed. With the large amount of statistical claims we\u2019re presented with regularly, it can feel overwhelming and like a lot of work to have to think about and filter each one but in reality doing so doesn’t have to be so hard or overwhelming.\u00a0<\/span><\/p>\n

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So let\u2019s revisit how we <\/span>build self-confidence in our ability to figure out and understand what\u2019s going on.<\/span>While Harford provides ten rules we can follow, he simplifies them into a \u201cgolden rule\u201d focused on staying open and curious.\u00a0 If we remain curious, statistical data can open up the world in a whole new way for us. The BBC made a short video highlighting the \u201cThree C\u2019s\u201d that help support a natural application of the ten rules: \u201cStay Calm, Get Context, Be Curious\u201d [6].\u00a0<\/span><\/p>\n

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Staying calm is about understanding the role our emotions play in decision-making. The Leadership Circle Profile, an assessment tool I\u2019ve used in my work, invites growth and development by moving leaders from a place of reaction to a creative response. When we operate solely on a gut feeling \u2013 the emotions, thoughts, and beliefs it stirs \u2013 we\u2019re more likely to navigate the world from a place of misalignment with our core values, than if we were to pause to discern a more creative response. To respond vs react is a powerful distinction because it implies intentionality of thought, followed by action.\u00a0 Thus highlighting how we aren’t truly using our brains when we react. Again, this begs the question \u201cHow could we truly trust ourselves to be able to understand and leverage statistics if we aren’t using our brains in much of our decision-making?\u201d<\/span><\/p>\n

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If we can pause for a moment in the \u201ccalming\u201d stage we can then exercise the brain power to \u201cGet Context\u201d by looking at some of the variables mentioned above and comprehensively reviewing research findings. We then build upon that by exploring the \u201ccuriosities\u201d it births. <\/span>To remain curious is about inviting a child-like wonder into your day-to-day life and using that to explore the world more deeply, asking questions of everything you engage in. Inquiry is vital to growth. The day we stop asking questions is the day our lives cease to have much value because we will have stopped thinking for ourselves in exchange for the easier route of blind acceptance.\u00a0<\/span><\/p>\n

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So, what am<\/span> I <\/span><\/i>doing with all of this?\u00a0 I\u2019m asking questions and getting curious as it relates to my research. Already this has begged me to re-examine how I’ve framed my research question and how I\u2019ll interpret the findings from my literature reviews.\u00a0<\/span><\/p>\n

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How are you staying curious when it comes to your research?<\/span><\/p>\n

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Footnotes<\/span><\/p>\n

[1]Tim Harford, \u201cThe Data Detective: Tim Harford,\u201d Youtube (Youtube, November 5, 2021), <\/span>https:\/\/www.youtube.com\/watch?v=rmqi09ldF_E<\/span><\/a>.<\/span><\/p>\n

[2]Harford, Tim. <\/span>Data Detective: Ten Easy Rules to Make Sense of Statistics.<\/span><\/i> New York City, New York, US: Riverhead Books, 2022.<\/span><\/p>\n

[3]Clarke, Geraint. \u201cWhy You Can\u2019t Trust Statistics.\u201d Medium, June 14, 2021. https:\/\/medium.com\/one-minute-wonders\/you-cant-blindly-trust-all-statistics-69c92348d31d.<\/span><\/p>\n

[4]Arley. \u201cYour Daily Science: Why You Can\u2019t Always Trust Statistics.\u201d Medium, July 10, 2023. https:\/\/medium.com\/@ArleyWrites\/your-daily-science-why-you-cant-always-trust-statistics-c4a4f666a902.<\/span><\/p>\n

[5]Seife, Charles. <\/span>Proofiness: The Dark Arts of Mathematical Deception<\/span><\/i>. New York: Viking, 2011.<\/span><\/p>\n

[6]BBC Ideas. \u201cWhen Can You Trust Statistics? | BBC Ideas.\u201d <\/span>YouTube<\/span><\/i>, June 17, 2021. https:\/\/www.youtube.com\/watch?v=aPh3E8IoHzk.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

In a world where we tend to be either overly suspicious or not suspicious enough of the research and statistics at the core of many of our beliefs, Tim Harford\u2019s\u00a0 \u201cThe Data Detective: Ten Easy Rules to Make Sense of Statistics\u201d\u00a0 offers a solution for how to find a healthy balance where we learn to […]<\/p>\n","protected":false},"author":209,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[1],"tags":[3043,2967],"class_list":["post-35623","post","type-post","status-publish","format-standard","hentry","category-uncategorized","tag-harford","tag-dlgp03","cohort-dlgp03"],"acf":[],"_links":{"self":[{"href":"https:\/\/blogs.georgefox.edu\/dlgp\/wp-json\/wp\/v2\/posts\/35623","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.georgefox.edu\/dlgp\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.georgefox.edu\/dlgp\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.georgefox.edu\/dlgp\/wp-json\/wp\/v2\/users\/209"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.georgefox.edu\/dlgp\/wp-json\/wp\/v2\/comments?post=35623"}],"version-history":[{"count":2,"href":"https:\/\/blogs.georgefox.edu\/dlgp\/wp-json\/wp\/v2\/posts\/35623\/revisions"}],"predecessor-version":[{"id":35625,"href":"https:\/\/blogs.georgefox.edu\/dlgp\/wp-json\/wp\/v2\/posts\/35623\/revisions\/35625"}],"wp:attachment":[{"href":"https:\/\/blogs.georgefox.edu\/dlgp\/wp-json\/wp\/v2\/media?parent=35623"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.georgefox.edu\/dlgp\/wp-json\/wp\/v2\/categories?post=35623"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.georgefox.edu\/dlgp\/wp-json\/wp\/v2\/tags?post=35623"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}